Machine-readable program registry
AI program registry
Source-checked AI education program profiles generated from the Academies.ai machine-readable registry.
Introduction to Generative AI Learning Path Specialization
Google Cloud's Introduction to Generative AI Learning Path Specialization is a four-course program on Coursera. It introduces generative AI, large language models and responsible-AI principles, then considers how organizations can apply those principles. Learning includes interactive quizzes with immediate feedback. Coursera labels it Intermediate and says some related experience is required without naming a particular language or qualification. Completion earns a shareable Google Cloud career certificate. Consider it for conceptual foundations and organizational responsibility, rather than a sequence centered on building generative-AI applications.
- Duration
- Hero: 4 weeks at 10 hours per weekfour course estimates total 4 hours 16 minutes. Conflicting provider estimates with distinct scopes, not completion guarantees.
- Level
- Intermediate
- Format
- Online, flexible, self-paced four-course specialization taught in English with 28 languages available. Applied learning consists primarily of interactive quizzes with immediate feedback on concepts and terminology.
- Credential
- Career certificate
- Prerequisites
- Some related experience required; the program page does not specify a particular language, tool, credential or formal prerequisite.
Sources ↗
- Duration · https://www.coursera.org/specializations/introduction-to-generative-ai
- Official program page · https://www.coursera.org/specializations/introduction-to-generative-ai
- Credential details · https://www.coursera.org/about/terms
- Cost terms · https://www.coursera.org/courseraplus/special/cplus-monthly-august-2026-global
Artificial Intelligence Graduate Certificate
Stanford Online's Artificial Intelligence Graduate Certificate requires four graduate courses selected from its required and elective lists within three academic years. The program is online; most students take one to two years, with an estimated fifteen to twenty hours per week for each course. Applicants need a bachelor's degree, a qualifying undergraduate GPA and preparation in mathematics, probability and programming. A grade of B or better is required in every selected course. The published tuition range is separate from document and possible drop fees. This is not an introductory course for a learner without the stated technical prerequisites, and current course availability can limit immediate enrollment.
- Duration
- Most students complete in 1-2 yearsfour courses must be completed within three academic years. Average 15-20 hours per week per course.
- Level
- Graduate
- Format
- 100% online graduate coursesdelivery and availability depend on the selected course
- Credential
- Graduate certificate
- Prerequisites
- Conferred bachelor's degree with undergraduate GPA 3.0 or better; College-level calculus and linear algebra, including multivariate derivatives and matrix/vector notation and operations; Probability theory and basic continuous/discrete probability distributions; Programming experience and Linux command-line workflows.
Sources ↗
Machine Learning Specialization
Machine Learning Specialization is a beginner-level, three-course program created by DeepLearning.AI and Stanford Online. It covers supervised learning, neural networks, decision trees, clustering, recommenders and reinforcement learning, using Python-based tools including NumPy, scikit-learn and TensorFlow. Learners should understand basic coding and high-school arithmetic and algebra. DeepLearning.AI Pro offers an assessment-based certificate route, while Coursera has separate payment and certificate conditions. This is not a no-code business overview. Check the selected platform's award requirements and Coursera certificate-eligibility window before paying.
- Duration
- Publisher content: 94h58m. Publisher pacing: about 10 weeks at 5 hours/weekCoursera pacing: 2 months at 10 hours/week, with course estimates 33/34/28 hours. Different provider estimates, not a completion guarantee.
- Level
- Beginner
- Format
- Online, self-paced three-course specialization with video lessons, code examples and graded assignments.
- Credential
- Course completion certificate
- Prerequisites
- Basic coding knowledge (for loops, functions and if/else statements) plus high-school arithmetic and algebra. Additional math is explained along the way; no heavy math background or deep coding experience is required.
Sources ↗
- Duration · https://www.deeplearning.ai/courses/machine-learning-specialization/
- Official program page · https://www.deeplearning.ai/courses/machine-learning-specialization/
- Credential details · https://www.coursera.org/specializations/machine-learning-introduction
- Cost terms · https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
AWS Certified Machine Learning Engineer - Associate
AWS Certified Machine Learning Engineer - Associate assesses production machine-learning work on AWS through the MLA-C01 exam. Its domains cover data preparation, model development, deployment and orchestration, and monitoring, maintenance and security. AWS describes an intended candidate with at least one year of relevant SageMaker and AWS experience; that recommendation is not a formal enrollment prerequisite. The exam has 65 questions and a 130-minute sitting time, separate from preparation. English MLA-C01 testing ended on September 28, 2026, while the listed Asian-language versions continue until MLA-C02 general availability. Do not treat that transition as early expiry of an earned credential. Choose this for AWS engineering assessment, not a beginner teaching course.
- Price
- USD 150USD 150 for one MLA-C01 attempt. The last English test day was September 28, 2026; Japanese, Korean and Simplified Chinese continue until MLA-C02 general availability. Preparation is separate.
- Duration
- 130 minutes for the exam assessmentnot preparation time
- Level
- Associate
- Format
- Proctored certification examQuestions: 65.
- Credential
- industry certification
- Prerequisites
- Provider describes an intended candidate with at least 1 year using Amazon SageMaker and other AWS ML-engineering services; the guide also recommends at least 1 year in a related role. No formal prerequisite is stated.
Sources ↗
- Price : https://aws.amazon.com/certification/certified-machine-learning-engineer-associate/
- Duration : https://aws.amazon.com/certification/certified-machine-learning-engineer-associate/
- Official program page : https://aws.amazon.com/certification/certified-machine-learning-engineer-associate/
- Modules or exam domains : https://docs.aws.amazon.com/aws-certification/latest/machine-learning-engineer-associate-01/machine-learning-engineer-associate-01.html
- Credential details : https://aws.amazon.com/certification/benefits/
- Credential details : https://aws.amazon.com/certification/recertification/
Databricks Certified Generative AI Engineer Associate
Databricks Certified Generative AI Engineer Associate assesses the design and implementation of LLM-enabled solutions using Databricks. Its blueprint covers application design, data preparation, development, deployment, governance, evaluation and monitoring. The provider recommends related training and at least six months of relevant practical experience, while listing no formal prerequisites. The proctored exam has 45 scored multiple-choice questions and a 90-minute time limit; unscored items may also appear, with additional time factored in. Its advertised registration fee is USD 200, normalized from the official US page's dollar display. The credential lasts two years and requires the current exam for recertification. It is not a substitute for learning the implementation tasks or a general, vendor-neutral course.
- Price
- USD 200USD 200 for the stated exam registration scope. The official US page displays $200; USD is normalized under the accepted US-source rule, not quoted as a literal ISO label. Preparation and repeat-attempt costs are separate.
- Duration
- 90 minutes for the exam assessmentnot preparation time
- Level
- Associate
- Format
- Proctored certification exam
- Credential
- proctored certification
- Prerequisites
- None, but related training is highly recommended; 6+ months of relevant hands-on experience is recommended.
Sources ↗
- Price · https://www.databricks.com/learn/certification/genai-engineer-associate
- Duration · https://www.databricks.com/learn/certification/genai-engineer-associate
- Official program page · https://www.databricks.com/learn/certification/genai-engineer-associate
- Credential details · https://www.databricks.com/learn/training/certification
NVIDIA-Certified Professional: Generative AI LLMs
NVIDIA-Certified Professional: Generative AI LLMs assesses technical work across LLM architecture, prompting, data preparation, optimization, fine-tuning, evaluation, GPU acceleration, deployment and monitoring. NVIDIA brands it Professional while describing the credential as intermediate-level. It expects two to three years of practical AI and machine-learning experience with LLMs; familiarity with NVIDIA platforms is useful but not strictly required. The remotely proctored exam has 60–70 questions and a 120-minute sitting time, not a preparation estimate. The exam fee is USD 200 on the reviewed US page. This is not a first introduction to AI.
- Price
- USD 200USD 200 for the stated exam registration scope. The official US page displays $200; USD is normalized under the accepted US-source rule, not quoted as a literal ISO label. Preparation and repeat-attempt costs are separate.
- Duration
- 120 minutes for the exam assessmentnot preparation time
- Level
- Professional (provider also describes the credential as intermediate-level)
- Format
- Proctored certification examQuestions: 60-70.
- Credential
- professional certification
- Prerequisites
- Provider expects 2-3 years of practical AI/ML experience working with LLMs and detailed technical familiarity; NVIDIA-platform familiarity is beneficial but not strictly required.
Sources ↗
- Price : https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-professional/
- Duration : https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-professional/
- Official program page : https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-professional/
- Credential details : https://www.nvidia.com/en-us/learn/certification/#faq
IBM AI Developer Professional Certificate
The IBM AI Developer Professional Certificate is a beginner-oriented ten-course sequence on Coursera focused on building AI-powered applications. The curriculum spans software engineering, AI and generative AI foundations, prompt engineering, web development, Python, Flask, and application projects. The provider banner indicates no prior AI or programming experience is needed to begin. The banner estimates completion in six months at four hours per week, while the FAQ estimates six to eight months at three to five hours per week. The program distinguishes between earning a Professional Certificate from Coursera and a separate digital badge from IBM. It serves as a structured introduction to application building.
- Price
- Coursera Plus Monthly : USD 59 / month regularNo promotional price stated.
Region, access and offer terms
United States on 2 October 2026
No promotional price stated in the checked source.
Monthly USD 59 and annual USD 399 are alternative recurring access plans. There is no guaranteed total completion period. IBM AI Developer Professional Certificate page explicitly displays Included with Coursera Plus.
- Duration
- The provider page banner estimates 6 months at 4 hours per week. The FAQ estimates 6-8 months at 3-5 hours per week, noting that each course takes 4-6 weeks.
- Level
- Beginner
- Format
- Online, flexible, self-paced 10-course Professional Certificate with hands-on labs and projects.
- Credential
- Professional Certificate
- Prerequisites
- The banner states no prior AI or programming experience is required. The FAQ outlines progression expectations, stating 'courses 1-5' do not require programming knowledge, while the 'final two courses' require proficiency in programming and software engineering principles.
Sources ↗
- Price : https://www.coursera.org/courseraplus
- Duration : https://www.coursera.org/professional-certificates/applied-artifical-intelligence-ibm-watson-ai
- Official program page : https://www.coursera.org/professional-certificates/applied-artifical-intelligence-ibm-watson-ai
- Provider subscription terms : https://www.coursera.org/courseraplus
IBM AI Product Manager Professional Certificate
IBM AI Product Manager Professional Certificate combines product-management foundations with introductory AI and generative-AI work across ten courses. Its sequence covers stakeholders, product strategy and delivery, prompting, foundation models, and building AI-powered products. Coursera labels it beginner level, requires no prior experience, and estimates three months at ten hours per week. Treat that as a learning schedule, not a fixed purchase duration. The page describes a project portfolio and a shareable Professional Certificate from IBM, and explicitly identifies Coursera Plus eligibility. It is a product-management route rather than a replacement for deep model-development training. Check the recurring plan and completion requirements separately; the reviewed evidence does not state credential expiry or renewal.
- Price
- Coursera Plus Monthly : USD 59 / month regularNo promotional price stated.
Region, access and offer terms
United States on 2 October 2026
No promotional price stated in the checked source.
Monthly USD 59 and annual USD 399 are alternative recurring access plans. There is no guaranteed total completion period. IBM AI Product Manager Professional Certificate page explicitly displays Included with Coursera Plus.
- Duration
- 3 months to complete at 10 hours a week
- Level
- Beginner
- Format
- Online, flexible, self-paced 10-course Professional Certificate with hands-on activities and projects.
- Credential
- Professional Certificate
- Prerequisites
- No prior experience required.
Sources ↗
Generative AI for Everyone
Generative AI for Everyone is a beginner course from DeepLearning.AI for understanding generative-AI capabilities, tools, projects, business strategy and social implications. It requires no coding skills or prior AI knowledge. The publisher lists 5 hours and 1 minute, 32 video lessons, two code examples and six graded assignments marked Pro; these are workload and content descriptions, not a completion guarantee. Its three sections cover an introduction, generative-AI projects, and business and society. A certificate on the publisher platform requires Pro access. Coursera is a separate enrollment route; check its current access period and certificate eligibility before paying. Choose this for broad orientation, not sustained engineering implementation practice.
- Price
- DeepLearning.AI Pro · USD 50/month for course content, billed monthly at the regular price. (a time-limited promotion was displayed on 6 September 2026)(see provider page)
Provider pricing observations recorded 2026-09-06. Public logged-out publisher pages identify USD; taxes may apply by location. Pro's monthly panel shows USD50/month reference. A time-limited promotion was displayed on 6 September 2026. A regular annual charged total is not stated. These access payments do not establish a completion cost. · Official pricing - Duration
- Publisher lists 5 hours 1 minute of contentthe separate Coursera route estimates approximately 6 hours. Not a guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Online course with 32 video lessons, 2 code examples, hands-on exercises and 6 graded assignments marked PROCoursera version is self-paced.
- Credential
- Course completion certificate
- Prerequisites
- No coding skills or prior knowledge of AI required.
Sources ↗
- Price : https://www.deeplearning.ai/membership
- Duration : https://www.deeplearning.ai/courses/generative-ai-for-everyone/
- Official program page : https://www.deeplearning.ai/courses/generative-ai-for-everyone/
- Provider subscription terms : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-much-does-the-deeplearning.ai-pro-membership-cost
- Credential details : https://www.coursera.org/learn/generative-ai-for-everyone
Google AI Essentials
Google AI Essentials is a beginner, self-paced five-course specialization for using generative AI in everyday work. Its courses cover AI fundamentals, productivity tools, prompting, responsible use and keeping current. No experience is required. Hands-on activities include generating text and images, planning tasks and evaluating AI outputs. Completion earns a shareable Google career certificate, not a professional certification. USD 49 per month after an initial seven-day free trial, as shown in the United States on 3 October 2026. One month of access is not a completion guarantee. Consider it for practical workplace use, not advanced engineering or a detailed organizational AI strategy.
- Price
- Google AI Essentials monthly subscription : USD 49 / month regularNo promotional price stated.
Region, access and offer terms
U.S. and Canada; other countries may have lower local pricing shown at Coursera checkout.
No promotional price stated in the checked source.
Seven-day trial stated. This single-program route is separate from Coursera Plus. USD 49 per month after an initial seven-day free trial, as shown in the United States on 3 October 2026. One month of access is not a completion guarantee.
- Duration
- Under 5 hours on Google's program page; under 10 hours in the Coursera program descriptionGoogle's program page lists fewer than 5 hours to complete and says "In under 5 hours"; the Coursera page says "In under 10 hours" and shows a 4-hour top-level label. The five Coursera course estimates total 8 hours. These are provider study estimates; no single guaranteed total or weekly workload is inferred.
- Level
- Beginner
- Format
- Online, self-paced five-course specialization with flexible scheduling.
- Credential
- certificate
- Prerequisites
- No experience required.
Sources ↗
- Price : https://grow.google/ai-essentials/
- Duration : https://grow.google/ai-essentials/
- Official program page : https://www.coursera.org/specializations/ai-essentials-google
- Provider subscription terms : https://grow.google/ai-essentials/
- Access checked on 4 September 2026: one access method opened a regional homepage, while a web reader returned the AI Essentials course page at the original official address.
AWS Certified AI Practitioner (AIF-C01)
A foundational AWS certification for people who use or discuss AI and machine-learning solutions in an AWS context. The exam covers AI/ML concepts, generative AI, foundation-model applications, responsible AI, and related security and governance topics. It does not by itself verify production engineering ability.
- Price
- USD 100Before booking costs
- Duration
- 90 minutes (exam only; not preparation time)
- Level
- Foundational
- Format
- Certification examPearson VUE test center or online proctored
- Credential
- AWS Certification
- Prerequisites
- AWS describes familiarity with AI/ML on AWS and up to six months of exposure as the target candidate profile, not a mandatory experience duration. Candidates must be at least 13; ages 13–17 require parent or guardian consent.
Sources ↗
- Price : https://aws.amazon.com/certification/certified-ai-practitioner/
- Duration : https://aws.amazon.com/certification/certified-ai-practitioner/
- Official program page : https://aws.amazon.com/certification/certified-ai-practitioner/
- Modules or exam domains : https://docs.aws.amazon.com/aws-certification/latest/ai-practitioner-01/ai-practitioner-01.html
- Credential details : https://aws.amazon.com/certification/faqs/
- Credential details : https://aws.amazon.com/certification/recertification/
Google Cloud Generative AI Leader
A business-oriented Google Cloud certification for professionals in any job role. It assesses generative-AI fundamentals, Google Cloud offerings, techniques for improving model output, and business strategy. Google publishes no prerequisite and does not require hands-on technical experience, so the credential should not be treated as proof of engineering ability.
- Price
- USD 99One exam attempt. Explicit USD is supported by the Spanish page for the same Generative AI Leader exam. The English US capture on 27 September 2026 displays $99 plus tax where applicable; the USD attribution above retains its historical Spanish-source date.
- Duration
- 90 minutes (exam sitting only; not preparation time)
- Format
- Certification examonline-proctored or onsite-proctored
- Credential
- Google Cloud Certification
- Prerequisites
- None
Sources ↗
- Price · https://cloud.google.com/learn/certification/generative-ai-leader?hl=es
- Duration · https://cloud.google.com/learn/certification/generative-ai-leader
- Official program page · https://cloud.google.com/learn/certification/generative-ai-leader
- Credential details · https://support.google.com/cloud-certification/answer/9908350?hl=en
- Credential details · https://support.google.com/cloud-certification/answer/13258004?hl=en
- Credential details · https://cloud.google.com/certification/terms
Introduction to Generative AI
Introduction to Generative AI is a 45-minute introductory microlearning course on Google Skills. It explains generative AI, its uses, and how it differs from traditional machine learning, and covers Google tools for developing generative AI apps. The page advertises a badge. Consider it for an initial overview, not for in-depth engineering training or evidence of production implementation skills.
- Duration
- 45 minutes
- Level
- Introductory
- Format
- Microlearning course
- Credential
- badge
Sources ↗
- Duration : https://www.skills.google/course_templates/536
- Official program page : https://www.skills.google/course_templates/536
- Rechecked on 6 September 2026: the official Google Skills page opened and showed the course overview, named lessons, four required quizzes and a reading. The access exception recorded on 4 September is historical, not the result of this check.
IBM AI Engineering Professional Certificate
An online IBM program on Coursera covering machine learning, deep learning, big-data workflows, neural-network frameworks, and applied projects. It is aimed at technical learners and awards a professional learning credential, not an academic degree or independent proof of production work experience.
- Price
- Coursera Plus Monthly · USD 59 / month regularNo promotional price stated.
Region, access and offer terms
Outside the US, local currency and pricing are shown at checkout.
No promotional price stated in the checked source.
Lowest exact verified upfront plan route only for programs whose own page independently shows Included with Coursera Plus; not a global-cheapest claim and not a guaranteed completion period. The IBM AI Engineering program page independently displays Included with Coursera Plus.
- Duration
- 4 months at 10 hours a week
- Level
- Intermediate
- Format
- Online, self-paced multi-course program
- Credential
- Professional Certificate
- Prerequisites
- Working knowledge of Python and Jupyter Notebooks, plus high-school mathematics or mathematics for machine learning.
Sources ↗
- Duration · https://www.coursera.org/professional-certificates/ai-engineer
- Official program page · https://www.coursera.org/professional-certificates/ai-engineer
- Provider subscription terms · https://www.coursera.org/courseraplus/special/cplus-monthly-august-2026-global
- Credential details · https://www.credly.com/org/ibm/badge/ibm-ai-engineering-professional-certificate-v3
MIT Sloan AI Essentials: Accelerating Impactful Adoption
MIT Sloan offers this executive-education course for leaders connecting AI literacy with strategy, adoption, governance and organizational decisions. Activities include prompt engineering and agent creation. The live-online offering is December 14–16, 2026, with three days at five hours per day and tuition of USD 5,700. The separate in-person offering lists dates coming soon and tuition of USD 5,500, as shown in the United States on 26 September 2026. The course awards a certificate of course completion and counts toward the Executive Certificate in Digital Business; it does not award that full certificate by itself. The listed modules follow the in-person sample schedule, which is subject to change. Verify the selected offering before booking.
- Price
- USD 5700USD 5,700 tuition for the December 14-16, 2026 live-online offering, as shown in the United States on 26 September 2026. A separate in-person offering has dates coming soon and tuition USD 5,500. Confirm the selected offering; no all-in attendance cost is established.
- Duration
- Live online: December 14-16, 2026, three days at five hours/day. In-person dates are listed as coming soon in the 26 September capture.
- Format
- Executive education coursein-person or live online depending on selected offering
- Credential
- Certificate of course completion
- Prerequisites
- The course addresses leaders, executives, nontechnical managers and business professionals. No formal prerequisite requirement is stated in the saved source.
Sources ↗
NVIDIA-Certified Associate: Generative AI LLMs (NCA-GENL)
An entry-level, associate NVIDIA certification covering foundational concepts for developing, integrating, and maintaining generative-AI and LLM applications with NVIDIA solutions. The exam page lists 50-60 multiple-choice questions and a 1-hour duration; NVIDIA's certification FAQ describes remote and in-person proctoring for its exams.
- Price
- USD 125US-page price; regional terms may differ
- Duration
- 60 minutes
- Level
- Associate
- Format
- Proctored certification examthe exam page lists 50-60 multiple-choice questions and a 1-hour duration. The NVIDIA certification FAQ describes online remote proctoring and in-person testing with an NVIDIA testing partner for its exams.
- Credential
- NVIDIA Certification with digital badge and optional certificate
- Prerequisites
- Basic understanding of generative AI and large language models.
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-associate/
- Duration · https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-associate/
- Official program page · https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-associate/
- Credential details · https://www.nvidia.com/en-us/learn/certification/
AI for Everyone
AI for Everyone is a beginner, non-technical course from DeepLearning.AI, taught by Andrew Ng. It explains AI terminology, realistic capabilities, project workflows, company AI strategy and social implications. No technical or business background is required. The publisher lists thirty-five video lessons, four Pro graded assignments and six hours fifty-four minutes of content; Coursera separately estimates seven hours. The publisher's pacing FAQ gives four weeks at two to three hours weekly. Pro and Coursera offer distinct certificate and payment routes. The Coursera certificate-eligibility window is separate from Pro access. Consider it for conceptual and organizational understanding, not hands-on prompting instruction or programming practice.
- Price
- DeepLearning.AI Pro · USD 50/month for course content, billed monthly at the regular price. (a time-limited promotion was displayed on 6 September 2026)(see provider page)
Provider pricing observations recorded 2026-09-06. Public logged-out publisher pages identify USD; taxes may apply by location. Pro's monthly panel shows USD50/month reference. A time-limited promotion was displayed on 6 September 2026. A regular annual charged total is not stated. These access payments do not establish a completion cost. · Official pricing - Duration
- 6h54m in the publisher overview; Coursera separately estimates 7 hoursThe publisher pacing FAQ says about 4 weeks at 2–3 hours per week. These are estimates on different bases, not a completion guarantee.
- Level
- Beginner
- Format
- Online, self-paced course with 35 video lessons and 4 graded assignments on the Pro routeCoursera enrollment is separate.
- Credential
- Course completion certificate
- Prerequisites
- No technical or business background required; no prior experience required.
Sources ↗
Professional Machine Learning Engineer Certification
Professional Machine Learning Engineer Certification is the title of a Google Skills learning path managed by Google Cloud, not the certification exam itself. Its 17 activities combine on-demand courses, labs, and skill badges focused on designing, building, operating, optimizing, and maintaining machine learning systems on Google Cloud. The path emphasizes applied work with Google Cloud technologies and describes its material as advanced. It points learners toward preparation for the separate Professional Machine Learning Engineer exam. Consider it when your objective is structured learning for that cloud-specific engineering role. It is not a substitute for taking the exam, nor the natural choice for a reader seeking only a non-technical introduction to AI.
- Format
- Learning path with on-demand courses, labs, and skill badgesnot the certification exam
IBM Generative AI Engineering Professional Certificate
IBM Generative AI Engineering Professional Certificate is a beginner-level, online series of 16 courses offered by IBM on Coursera. The overview estimates six months at six hours per week, with self-paced study. Basic computer literacy is the stated background requirement. The curriculum moves from AI concepts and Python through data analysis, machine learning, deep learning, transformer models, fine-tuning, and applications using RAG and LangChain. Hands-on work includes Python applications, model training, and a guided generative AI application project. Completion provides a shareable IBM certificate. Consider it if you want a multi-course introduction to technical generative AI development; it is not for someone seeking only a short, non-coding overview of AI tools.
- Price
- Coursera Plus Monthly : USD 59 / month regularNo promotional price stated.
Region, access and offer terms
United States on 2 October 2026
No promotional price stated in the checked source.
Monthly USD 59 and annual USD 399 are alternative recurring access plans. There is no guaranteed total completion period. IBM Generative AI Engineering Professional Certificate page explicitly displays Included with Coursera Plus.
- Duration
- Estimated 6 months at 6 hours a weekself-paced
- Level
- Beginner
- Format
- Online, self-paced 16-course series
- Credential
- Professional Certificate
- Prerequisites
- Basic computer literacy; no prior experience required.
Sources ↗
- Price : https://www.coursera.org/courseraplus
- Duration : https://www.coursera.org/professional-certificates/ibm-generative-ai-engineering
- Official program page : https://www.coursera.org/professional-certificates/ibm-generative-ai-engineering
- Provider subscription terms : https://www.coursera.org/courseraplus
AI Fundamentals
AI Fundamentals is a DataCamp learning track focused on AI concepts and their use at work. DataCamp estimates nine hours and states that no prerequisites or coding experience are needed. The visible course list covers AI for work, machine learning, large language models, generative AI, and ethics. The description includes interaction with AI applications and practice in collaboration and prompting. Completing the track provides a Statement of Accomplishment that can be shared on a professional profile. A separately advertised certification is not the same as track completion. Consider this track for conceptual understanding; it is not the right choice if you specifically need programming practice or an independently earned certification.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- Approximately 9 hours
- Level
- Beginner
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- No prerequisites or coding experience required.
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/ai-fundamentals
- Official program page · https://www.datacamp.com/tracks/ai-fundamentals
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
- Modules or exam domains · https://www.datacamp.com/courses/introduction-to-ai-for-work?variant=traditional
- Modules or exam domains · https://www.datacamp.com/courses/understanding-machine-learning
- Modules or exam domains · https://www.datacamp.com/courses/large-language-models-llms-concepts
- Modules or exam domains · https://www.datacamp.com/courses/generative-ai-concepts
- Modules or exam domains · https://www.datacamp.com/courses/ai-ethics
AI For Business Specialization
AI For Business Specialization is a four-course online program offered by the University of Pennsylvania on Coursera. It is labeled beginner level and requires no specific background. The courses address AI fundamentals for non-data scientists, marketing and finance applications, people management, and strategy and governance. Each module ends with an assessment, and two courses include peer-review exercises. Study is self-paced, and courses can be taken in any order. Completion provides a shareable career certificate from the University of Pennsylvania. Consider it for business applications and AI decision-making, not as a guaranteed route to university credit or as a substitute for advanced specialist training in a single technical field.
- Price
- Coursera Plus Monthly · USD 59 / month regular
Region, access and offer terms
Outside the US, local currency and pricing are shown at checkout.
Lowest exact verified upfront plan route only for programs whose own page independently shows Included with Coursera Plus; not a global-cheapest claim and not a guaranteed completion period. The Wharton AI For Business program page independently displays Included with Coursera Plus. Exact Wharton-specific logged-out checkout amount is not exposed.
- Level
- Beginner
- Format
- Online, self-paced specialization
- Credential
- Career Certificate
- Prerequisites
- No specific background required
Sources ↗
CS50’s Introduction to Artificial Intelligence with Python
CS50’s Introduction to Artificial Intelligence with Python combines lectures with programming projects on search, knowledge, uncertainty, optimization, learning, neural networks, and language. Harvard's OpenCourseWare presents seven weeks of material, studied at your own pace, rather than a guaranteed seven-week completion schedule. The stated prerequisites are CS50x or at least one year of Python experience. A free CS50 Certificate requires at least 70% on every project; an edX verified certificate is a separate paid route. There is no final exam. Choose it for project-based AI study using Python, not for a non-coding introduction or a credential earned simply by watching the lectures.
- Duration
- Seven weeks of material; self-paced. The FAQ estimates 10–20 hours for each week’s required problem sets; this is assignment workload, not total course completion time.
- Format
- Online self-paced
- Credential
- Certificate
- Prerequisites
- CS50x or at least one year of experience with Python.
Sources ↗
- Duration · https://cs50.harvard.edu/ai/
- Official program page · https://cs50.harvard.edu/ai/
- Modules or exam domains · https://cs50.harvard.edu/ai/weeks/0/
- Modules or exam domains · https://cs50.harvard.edu/ai/weeks/1/
- Modules or exam domains · https://cs50.harvard.edu/ai/weeks/2/
- Modules or exam domains · https://cs50.harvard.edu/ai/weeks/3/
- Modules or exam domains · https://cs50.harvard.edu/ai/weeks/4/
- Modules or exam domains · https://cs50.harvard.edu/ai/weeks/5/
- Modules or exam domains · https://cs50.harvard.edu/ai/weeks/6/
- Credential details · https://cs50.harvard.edu/ai/certificate/
- Credential details · https://cs50.harvard.edu/ai/faqs/
Associate AI Engineer for Developers
DataCamp's Associate AI Engineer for Developers track focuses on adding AI capabilities to software through APIs and open-source libraries. The listed curriculum covers the OpenAI API, prompting, Hugging Face, embeddings, Pinecone, LangChain, software engineering in Python, LLMOps, and Model Context Protocol. DataCamp lists 29 hours, ten courses, and two bonus projects. The formal prerequisites section states that there are no prerequisites, although the content involves Python and application development. Completing the track earns a shareable Statement of Accomplishment. The page also presents the track as preparation for a separate certification; completing the learning track should not be described as automatically earning that certification. Compare the listed tools with the applications you want to build.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 29 content hours
- Format
- Learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- The formal prerequisites section states there are no prerequisites for this track.
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/associate-ai-engineer-for-developers
- Official program page · https://www.datacamp.com/tracks/associate-ai-engineer-for-developers
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
- Credential details · https://support.datacamp.com/hc/en-us/articles/360017301033-DataCamp-Tracks
- Credential details · https://support.datacamp.com/hc/en-us/articles/360037240453-Statements-of-Accomplishment-Frequently-Asked-Questions
Associate AI Engineer for Data Scientists
DataCamp's Associate AI Engineer for Data Scientists track covers model development, evaluation, and deployment practices. Its curriculum includes supervised and unsupervised learning, PyTorch, explainable AI, responsible data management, LLMs, Llama 3, MLOps, Git, and Python testing. DataCamp lists 40 hours, thirteen courses, and two bonus projects. Track completion earns a shareable Statement of Accomplishment; the separately advertised certification is not automatically earned through that completion. The technical sequence is most relevant when you want to extend model-building work toward application and deployment concerns.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 40 hours of listed content
- Format
- Online DataCamp learning track13 courses plus 2 bonus projects (15 track items).
- Credential
- Statement of Accomplishment
- Prerequisites
- Formal prerequisites section: There are no prerequisites for this track. Context qualification: the audience section says it builds on existing machine-learning and Python knowledge.
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/associate-ai-engineer-for-data-scientists
- Official program page · https://www.datacamp.com/tracks/associate-ai-engineer-for-data-scientists
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
AI engineer
365 Data Science's AI engineer career track is an online, beginner-oriented sequence of ten courses with 32 hours of listed content. It starts with AI and Python foundations, then moves through data preprocessing, natural language processing, LLMs, vector databases, and application development. Named tools include LangChain, Pinecone, Streamlit, and OpenAI. The curriculum also includes speech recognition and using ChatGPT for data-science work. The provider describes practical projects and states that passing a final exam earns its AI engineer certification. That exam condition matters: consuming the learning content alone is not the stated award requirement. Treat the career language as the provider's positioning, not a guaranteed job outcome, and check enrollment terms separately from the content-hour estimate.
- Duration
- 32 hours of content
- Level
- Basic
- Format
- 100% online, self-paced career track
- Credential
- Provider-issued certification
- Prerequisites
- No enrollment prerequisites.
Sources ↗
Generative AI Essentials
Educative's Generative AI Essentials develops a conceptual understanding of generative models and how to work with them. Its six visible roadmap sections move from introductory concepts and NLP building blocks through foundation models, intelligent interaction, practical applications, and future developments. Topics include text preprocessing, neural networks, encoder-decoder models, prompting, and multimodal AI. The page lists 33 lessons, nine quizzes, and ten hours. A music-generation project is marked Premium, so access should be checked against the selected plan. The page displays a shareable Certificate of Completion and says more lessons must be completed to unlock it. It does not establish an exact certificate threshold or total purchase cost; those should not be guessed from the course length.
- Price
- Educative Standard · USD 298/year for course content, billed annually upfront. (a time-limited promotion was displayed on 23 September 2026)(see provider page)
Provider pricing observations recorded 2026-09-23. Annual displayed prices checked 23 September 2026; monthly observations retained from 4 September 2026. Authorized USD interpretation; provider display uses $. Regional pricing may differ. A time-limited promotion was displayed on 23 September 2026. · Official pricing - Duration
- 10 hours listed
- Format
- Online course
- Credential
- Certificate of Completion
Sources ↗
- Duration · https://www.educative.io/courses/generative-ai-essentials
- Official program page · https://www.educative.io/courses/generative-ai-essentials
- Provider subscription terms · https://www.educative.io/unlimited
- Credential details · https://www.educative.io/faq/certificates-faq
- Cost terms · https://www.educative.io/faq/subscription-faq
LLM Bootcamp
Educative's LLM Bootcamp focuses on decisions involved in designing, adapting and evaluating language-model applications. Its ten roadmap sections cover architectures, risks, transformers, vector databases, prompting, fine-tuning, LangChain, agentic workflows, retrieval-augmented generation and evaluation. The page lists 84 lessons, 85 quizzes, six Cloud Labs and sixteen hours. All six labs are marked Premium Plus; Standard covers course content, not those labs. Certificate claiming requires paid access, applicable assessments and sufficient interaction time. A claimed certificate is described as lifetime, subject to the legal-name exception. Consider it for application-design and evaluation topics, not as a non-coding business overview or an assumption that every activity is included in Standard.
- Price
- Educative Standard · USD 298/year for course content, billed annually upfront. (a time-limited promotion was displayed on 23 September 2026)(see provider page)
Provider pricing observations recorded 2026-09-23. Annual displayed prices checked 23 September 2026; monthly observations retained from 4 September 2026. Authorized USD interpretation; provider display uses $. Regional pricing may differ. A time-limited promotion was displayed on 23 September 2026. · Official pricing - Duration
- 16 hours listed
- Format
- Interactive online course with lessons, quizzes, and optional plan-gated Cloud Labs.
- Credential
- Certificate of Completion
Sources ↗
- Duration : https://www.educative.io/courses/llm-bootcamp
- Official program page : https://www.educative.io/courses/llm-bootcamp
- Provider subscription terms : https://www.educative.io/unlimited
- Credential details : https://www.educative.io/faq/certificates-faq
- Cost terms : https://www.educative.io/faq/subscription-faq
Microsoft Certified: Azure AI Fundamentals (AI-901)
AI-901 is the required exam for Microsoft Certified: Azure AI Fundamentals. The current study guide divides its scope into identifying AI concepts and capabilities, and implementing AI solutions using Microsoft Foundry. Microsoft describes candidates as early in AI solution development, but expects Python coding knowledge, foundational technical skills, and familiarity with Azure resources. This is therefore not a purely nontechnical overview. Microsoft's fundamentals exam policy specifies 45 minutes of assessment time, separate from preparation and appointment time. The observed fee is USD 99 with the United States exam region selected, not a worldwide price. Microsoft fundamentals certifications do not expire. Review the current AI-901 objectives rather than assuming older Azure AI Fundamentals preparation materials cover the updated scope.
- Price
- USD 99United States exam-proctoring region selected; single exam attempt. Not a global price. Confirm local pricing before booking.
- Duration
- 45 minutes (exam only; not preparation time)
- Format
- Certification exam
- Credential
- certification
- Prerequisites
- Conceptual knowledge of AI solutions in Azure and foundational technical skills; Python coding syntax and programming techniques; familiarity with Azure resources, REST APIs, SDKs, and CLIs.
Sources ↗
- Price · https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-901/
- Duration · https://learn.microsoft.com/en-us/credentials/support/exam-duration-exam-experience
- Official program page · https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-901/
- Modules or exam domains · https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-901
- Credential details · https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/
- Credential details · https://learn.microsoft.com/en-us/credentials/support/credential-expiration-policy
- Credential details · https://learn.microsoft.com/en-us/credentials/support/view-use-share-certificates-achievements
- Credential details · https://learn.microsoft.com/en-us/credentials/certifications/renew-your-microsoft-certification
- Cost terms · https://learn.microsoft.com/en-us/credentials/support/retake-policy
Microsoft Certified: Azure AI Apps and Agents Developer Associate (AI-103)
AI-103 leads to Microsoft Certified: Azure AI Apps and Agents Developer Associate, an intermediate credential for developing Azure AI solutions with Python and Microsoft Foundry. Microsoft expects experience building Python applications and familiarity with general AI, generative AI, and Azure services. The five exam domains cover planning and managing solutions, generative AI and agents, computer vision, text analysis, and information extraction. The current credential page gives 120 minutes for the assessment; that is not a preparation estimate. The observed fee is USD 165 for the United States exam region, with local pricing to be checked separately. The certification has one-year validity and a free online renewal route before expiry. Choose it for its Azure implementation scope, not as a no-code introduction.
- Price
- USD 165United States exam-proctoring region selected; single exam attempt. Not a global price. Confirm local pricing before booking.
- Duration
- 120 minutes (exam only; not preparation time)
- Level
- Intermediate
- Format
- Certification exam
- Credential
- certification
- Prerequisites
- Experience developing apps using Python; familiarity with general AI, generative AI, and Azure services.
Sources ↗
- Price · https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-apps-and-agents-developer-associate/
- Duration · https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-apps-and-agents-developer-associate/
- Official program page · https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-apps-and-agents-developer-associate/
- Modules or exam domains · https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-103
- Credential details · https://learn.microsoft.com/en-us/credentials/support/credential-expiration-policy
- Credential details · https://learn.microsoft.com/en-us/credentials/support/view-use-share-certificates-achievements
- Credential details · https://learn.microsoft.com/en-us/credentials/certifications/renew-your-microsoft-certification
- Cost terms · https://learn.microsoft.com/en-us/credentials/support/retake-policy
AI for Executives Program
In-person executive program on AI strategy, adoption, innovation and ethics, with hands-on exercises. It runs three days at 8.5 hours per day and displays a USD 6,500 programme fee. Intended for executives, senior managers, technical professionals and others tracking AI advances. It is not a fit for someone requiring remote delivery or a technical implementation curriculum. It grants a verified digital certificate of completion, not eligible for degree credit or CEUs. The provider recommends proficiency in written and spoken English; the teaching language and renewal terms are not stated. The next listed session is March 29–31, 2027.
- Price
- USD 6500Full published tuition for the displayed program/session. Taxes, travel and other incidental costs are not established; confirm the amount charged before enrolling. As shown in the United States on 27 September 2026. The next listed session is March 29–31, 2027.
- Duration
- 3 days; 8.5 hours/day The next listed session is March 29–31, 2027.
- Level
- Executive
- Format
- In-person
- Credential
- Certificate of Completion
Sources ↗
Agentic AI: Strategy, Applications, and Organizational Impact
Live online executive program on agentic-AI strategy, use-case scaling, organizational readiness, business value, governance and oversight. It runs five weeks at 4–5 hours per week and lists tuition of USD 3,550. It includes five live sessions, facilitator office hours, peer learning and a capstone strategy project, and requires no prior coding experience. It is not designed as hands-on technical implementation training. The verified digital completion certificate is emailed and can be shared on professional profiles; it provides no degree credit or CEUs. Language, external exam, expiry and renewal terms are not stated. No available dates are listed for the next program.
- Price
- USD 3550Full published tuition for the displayed program/session. Taxes, travel and other incidental costs are not established; confirm the amount charged before enrolling. As shown in the United States on 27 September 2026. No available dates are listed for the next program.
- Duration
- 5 weeks; 4–5 hours/week No available dates are listed for the next program.
- Level
- Executive
- Format
- Live online executive course
- Credential
- Certificate of Completion
- Prerequisites
- No prior coding or technical implementation experience is required.
Sources ↗
- Price · https://executive.berkeley.edu/programs/agentic-ai-strategy-applications-and-organizational-impact
- Duration · https://executive.berkeley.edu/programs/agentic-ai-strategy-applications-and-organizational-impact
- Official program page · https://executive.berkeley.edu/programs/agentic-ai-strategy-applications-and-organizational-impact
Berkeley Executive Program in AI and Digital Strategy
Eight-month blended executive program combining online learning and UC Berkeley campus activity. It covers digital innovation, strategic AI growth, enterprise transformation and emerging technologies, with two required short courses and a core strategy project. The displayed session costs USD 28,000. It is aimed at senior enterprise leaders; its blended format includes required in-person participation. Language, credential shareability and renewal terms are not stated. The listed session runs October 1, 2026–June 21, 2027.
- Price
- USD 28000Full published tuition for the displayed program/session. Taxes, travel and other incidental costs are not established; confirm the amount charged before enrolling. As shown in the United States on 27 September 2026. The listed session runs October 1, 2026–June 21, 2027.
- Duration
- 8 months The listed session runs October 1, 2026–June 21, 2027.
- Level
- Executive
- Format
- Blended
- Credential
- Certificate of Excellence in AI and Digital Strategy
Sources ↗
- Price · https://executive.berkeley.edu/programs/berkeley-executive-program-ai-and-digital-strategy
- Duration · https://executive.berkeley.edu/programs/berkeley-executive-program-ai-and-digital-strategy
- Official program page · https://executive.berkeley.edu/programs/berkeley-executive-program-ai-and-digital-strategy
Oxford Programme in Organising for AI
A 12-week cohort-based online executive programme for senior professionals organising AI strategy, governance and operating models. It combines recorded Oxford faculty content, five live cohort sessions, peer interaction, three modules and a required summative quiz. The total programme fee is USD 3,390, as shown in the United States on 25 September 2026; instalment amounts are not established in that capture. No coding background is required, but the stated audience generally has at least seven years of experience. It is not a degree. Weekly effort, taxes, credential expiry and native shareability are not established.
- Price
- USD 3390Total programme fee USD 3,390, as shown in the United States on 25 September 2026. Instalment options are mentioned, but no numeric instalment schedule is established in this US capture. Tax treatment is not stated.
- Duration
- 12 weeks
- Level
- Executive
- Format
- Cohort-based online learning: pre-recorded Oxford Saïd faculty videos, five cohort live sessions, discussions and peer interaction.
- Credential
- Certificate of completion from Saïd Business School, University of Oxford
- Prerequisites
- ['Designed for senior professionals with at least seven years of experience; slightly less may be reviewed case-by-case for a relevant strategic role.', 'Computer with internet access and standard web browser.', 'No coding skills or technical background required.', 'Eligibility Criteria: Undergraduate degree in any discipline; background in management, strategy, ops, tech or product.']
Sources ↗
AI for Business: Strategic Opportunities with AI
A five-day, in-person INSEAD executive programme on non-technical AI strategy, business applications, organisation design and working with AI experts. Tuition is session-specific: EUR 11,600 for the listed Fontainebleau sessions and SGD 16,600 for the listed Singapore session. The September 2026 Fontainebleau session is waitlisted. A 2025 promotional rate is stale and excluded. The programme contributes five eligible days toward a separate INSEAD Certificate in Global Management; the individual programme certificate title, assessment threshold, expiry and shareability are not fully stated.
- Price
- EUR 11,600 · 14–18 Sep 2026, Fontainebleau; SGD 16,600 · 23–27 Nov 2026, Singapore; EUR 11,600 · 19–23 Apr 2027, FontainebleauSession-specific tuition; use price_offers. Fees may change.
- Duration
- 5 days
- Level
- Executive
- Format
- In personFontainebleau or Singapore depending on session.
- Credential
- Programme certificate (exact title not stated on programme page)
Sources ↗
- Duration · https://www.insead.edu/executive-education/digital-transformation-ai/ai-business-strategic-opportunities-ai
- Official program page · https://www.insead.edu/executive-education/digital-transformation-ai/ai-business-strategic-opportunities-ai
- Cost terms · https://www.insead.edu/executive-education/digital-transformation-ai/ai-business-strategic-opportunities-ai/dates-fees
Transforming Your Business with AI
A fully online INSEAD executive programme with five content weeks, an Action Learning Project and peer review. Standard tuition is EUR 2,100. An optional EUR 690 Premium upgrade adds support and extends content access from six to nine months; that access period is not credential expiry. The curriculum covers AI strategy, governance, generative AI, RAG, guardrails, agents, fairness, privacy and organisation design. The certificate requires activities, minimum points, the final project and a satisfactory peer-reviewed grade. Credential expiry is not stated.
- Price
- EUR 2100Tuition fee for the Standard journey; fee subject to change. Optional upgrade adds EUR 690: Additional Learning Coach support, four extra weeks of ALP support after peer-review deadline, and 9-month rather than 6-month content access. Optional incremental upgrade; do not include in Standard tuition total unless selected.
- Duration
- 5 content weeks after a launch week, followed by 2 extra weeks for project completion and peer reviewpause week(s) may occur.
- Level
- Executive
- Format
- Fully onlineweekly asynchronous content plus occasional recorded live faculty calls, discussions and Learning Coach support.
- Credential
- Official Certificate of Completion from INSEAD
Sources ↗
- Price · https://www.insead.edu/executive-education/open-online-programmes/transform-business-ai
- Duration · https://www.insead.edu/executive-education/open-online-programmes/transform-business-ai
- Official program page · https://www.insead.edu/executive-education/open-online-programmes/transform-business-ai
Professional Machine Learning Engineer
Google Cloud's Professional Machine Learning Engineer certification assesses conventional and generative-AI engineering on Google Cloud, from low-code architecture and cross-team data management to model serving, pipelines and monitoring. It is a separate proctored exam, not the Google Skills preparation path. Google states no formal prerequisites but recommends three or more years of industry experience, including at least one year designing and managing Google Cloud solutions. The two-hour assessment has 50–60 questions; this is not a preparation-time estimate or a direct coding-skills test. Registration is USD 200, with preparation and repeat attempts separate. Choose it for experienced Google Cloud engineering assessment, and plan for the credential's two-year validity and renewal requirements.
- Price
- USD 200USD 200 for one certification exam registration/attempt. Optional preparation and repeat-attempt costs are separate. Currency is explicitly stated by the first-party Spanish localization.
- Duration
- 2 hours for the exam assessmentnot preparation time
- Level
- Professional
- Format
- Proctored certification examQuestions: 50–60.
- Credential
- industry certification
- Prerequisites
- None formally. Recommended: 3+ years of industry experience, including at least 1 year designing and managing solutions with Google Cloud.
Sources ↗
- Price : https://cloud.google.com/learn/certification/machine-learning-engineer?hl=es
- Duration : https://cloud.google.com/learn/certification/machine-learning-engineer
- Official program page : https://cloud.google.com/learn/certification/machine-learning-engineer
- Credential details : https://www.skills.google/paths/17?locale=en
- Credential details : https://support.google.com/cloud-certification/answer/9438208
- Credential details : https://support.google.com/cloud-certification/answer/9907853
- Credential details : https://support.google.com/cloud-certification/answer/9908350
AWS Certified Generative AI Developer - Professional (AIP-C01)
The AWS Certified Generative AI Developer - Professional (AIP-C01) is a certification from Amazon Web Services. It targets professionals with two years of experience building production-grade applications on AWS or open-source technologies, general AI or machine learning experience, and one year of hands-on experience implementing generative AI solutions. The 180-minute exam contains 65 scored questions and 10 unscored questions, using multiple-choice and multiple-response formats. It costs USD 300 for a single attempt, subject to regional pricing. No prior certification is required. Domains cover foundation-model integration, data management, compliance, implementation, AI safety, security, governance, operational efficiency, testing, and troubleshooting. The credential is valid for three years; recertification requires passing the current exam version.
- Price
- USD 300USD 300 for one attempt; foreign-exchange rates, regional pricing, optional preparation and repeat attempts are separate.
- Duration
- 180 minutes for the exam assessmentnot preparation time
- Level
- Professional
- Format
- Certification examQuestions: 65 scored questions plus 10 unscored questions.
- Credential
- industry certification
- Prerequisites
- No prior certification is required. Target profile: 2+ years building production-grade applications on AWS or open-source technologies, general AI/ML or data-engineering experience, and 1 year implementing generative-AI solutions.
Sources ↗
- Price : https://aws.amazon.com/certification/certified-generative-ai-developer-professional/
- Duration : https://aws.amazon.com/certification/certified-generative-ai-developer-professional/
- Official program page : https://aws.amazon.com/certification/certified-generative-ai-developer-professional/
- Credential details : https://docs.aws.amazon.com/aws-certification/latest/ai-professional-01.html
- Credential details : https://aws.amazon.com/certification/recertification/
- Credential details : https://aws.amazon.com/certification/faqs/
Exam AI-300: Operationalizing Machine Learning and Generative AI Solutions
Microsoft Exam AI-300: Operationalizing Machine Learning and Generative AI Solutions assesses MLOps and GenAIOps work on Azure. It covers MLOps infrastructure, the machine-learning model lifecycle, GenAIOps infrastructure, generative-AI observability and performance optimization. Expected background includes data science, Python, entry-level DevOps, GitHub Actions, command-line interfaces, Azure Machine Learning, Microsoft Foundry and infrastructure as code using Bicep or Azure CLI. A score of 700 or greater is required to pass. It earns Microsoft Certified: Machine Learning Operations Engineer Associate; the proctored English exam lasts 120 minutes, priced by proctoring region. Microsoft states that its associate, expert and specialty certifications expire annually and can be renewed by passing a free online Microsoft Learn assessment.
- Duration
- 120 minutes to complete the exam assessmentnot preparation time
- Level
- Intermediate
- Format
- Proctored certification exam
- Credential
- industry certification
- Prerequisites
- Expected background includes data science, Python, entry-level DevOps, GitHub Actions, CLIs, Azure Machine Learning, Microsoft Foundry and infrastructure as code with Bicep or Azure CLI.
Sources ↗
- Duration · https://learn.microsoft.com/en-us/credentials/certifications/exams/ai-300/
- Official program page · https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-300
- Credential details · https://learn.microsoft.com/en-us/credentials/certifications/renew-your-microsoft-certification-faq
- Credential details · https://learn.microsoft.com/en-us/credentials/support/view-use-share-certificates-achievements
NVIDIA-Certified Associate: Generative AI Multimodal (NCA-GENM)
The NVIDIA-Certified Associate: Generative AI Multimodal (NCA-GENM) is an entry-level credential offered by NVIDIA. It evaluates foundational skills for designing, implementing, and managing AI systems across text, image, and audio data. NVIDIA lists a basic understanding of generative AI as the prerequisite. The online, remotely proctored assessment requires a 60-minute sitting time, excluding any preparation. The English-language exam costs USD 125. Individuals who pass receive a digital badge and an optional certificate. The certification remains valid for two years and requires retaking the exam for recertification.
- Price
- USD 125USD 125 for the stated exam registration, normalized from $125 on the official US page; optional preparation and repeat attempts are separate.
- Duration
- 60 minutes for the exam assessmentnot preparation time
- Level
- Associate
- Format
- Proctored certification examQuestions: 50 on the overview; 50–60 in the details table.
- Credential
- industry certification
- Prerequisites
- Basic understanding of generative AI.
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/generative-ai-multimodal-associate/
- Duration · https://www.nvidia.com/en-us/learn/certification/generative-ai-multimodal-associate/
- Official program page · https://www.nvidia.com/en-us/learn/certification/generative-ai-multimodal-associate/
- Cost terms · https://www.nvidia.com/en-us/learn/certification/
NVIDIA-Certified Associate: AI Infrastructure and Operations (NCA-AIIO)
The NVIDIA-Certified Associate: AI Infrastructure and Operations (NCA-AIIO) is an entry-level credential offered by NVIDIA. It validates foundational concepts in AI computing infrastructure and operations. NVIDIA lists a basic understanding of data-center infrastructure as the prerequisite. The assessment consists of a remotely proctored online exam with 50 questions and a 60-minute sitting time. The English-language exam focuses on essential AI knowledge, AI infrastructure, and AI operations. The exam costs USD 125. A separate self-paced course taking approximately seven hours is recommended but not required. The credential is valid for two years, and successful candidates receive a digital badge and an optional certificate.
- Price
- USD 125USD 125 for the stated exam registration, normalized from $125 on the official US page; optional preparation and repeat attempts are separate.
- Duration
- 60 minutes for the exam assessmentnot preparation time
- Level
- Associate
- Format
- Proctored certification examQuestions: 50.
- Credential
- industry certification
- Prerequisites
- Basic understanding of data-center infrastructure.
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-operations-associate/
- Duration · https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-operations-associate/
- Official program page · https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-operations-associate/
- Cost terms · https://www.nvidia.com/en-us/learn/certification/
Databricks Certified Machine Learning Associate
This proctored certification exam assesses basic Databricks machine-learning tasks across Databricks Machine Learning, Data Processing, Model Development and Model Deployment. Its 48 scored items cover AutoML, Unity Catalog, MLflow, feature engineering, model training and deployment. The 90-minute exam sitting is not a preparation estimate. No prerequisite is mandatory; course attendance and six months of hands-on experience are recommended. The guide lists four self-paced preparation courses separately, without establishing training inclusion in the $200 registration fee. The credential lasts two years and requires the full current exam for recertification. This assessment does not provide AWS deployment instruction; the passing threshold and preparation duration are unstated.
- Price
- USD 200As shown in the United States on 25 September 2026, the guide lists a $200 registration fee for one exam attempt. Our editorial rule reads a dollar sign on a US official page as USD, so this is shown as USD 200; the PDF does not print an ISO currency code. Preparation, repeat attempts and tax are not established as included.
- Duration
- 90 minutes for the exam assessmentnot preparation time
- Level
- Associate
- Format
- Proctored certification examQuestions: 48 scored items.
- Credential
- industry certification
- Prerequisites
- No prerequisite required. Course attendance and six months of hands-on experience are highly recommended, with working Python, scikit-learn, SparkML, Unity Catalog and related data-management knowledge.
Sources ↗
- Price · https://www.databricks.com/sites/default/files/2025-02/databricks-certified-machine-learning-associate-exam-guide-1-mar-2025.pdf
- Duration · https://www.databricks.com/sites/default/files/2025-02/databricks-certified-machine-learning-associate-exam-guide-1-mar-2025.pdf
- Official program page · https://www.databricks.com/sites/default/files/2025-02/databricks-certified-machine-learning-associate-exam-guide-1-mar-2025.pdf
Databricks Certified Machine Learning Professional
The Databricks Certified Machine Learning Professional credential assesses a candidate's ability to design, implement, and manage enterprise-scale machine learning on Databricks. The assessment is a 120-minute online-proctored exam featuring 59 scored multiple-choice questions and costs USD 200. Assessed domains include scalable SparkML pipelines, distributed training, advanced MLflow, MLOps testing, automated retraining, Lakehouse Monitoring, and model serving. Databricks requires no prerequisites, but highly recommends one year of hands-on experience and knowledge of Python, scikit-learn, and SparkML. The certification is valid for two years, and recertification requires passing the current exam. The passing threshold, preparation time, and availability of a digital badge are not disclosed in the official exam guide.
- Price
- USD 200USD 200 for one attempt, plus applicable taxes as required per local law; optional preparation and repeat attempts are separate.
- Duration
- 120 minutes for the exam assessmentnot preparation time
- Level
- Professional
- Format
- Proctored certification examQuestions: 59 scored questions.
- Credential
- industry certification
- Prerequisites
- No prerequisite required. Course attendance and one year of hands-on Databricks experience are highly recommended, plus Python, scikit-learn, SparkML, MLflow, Lakehouse Monitoring and Model Serving knowledge.
Sources ↗
- Price · https://www.databricks.com/sites/default/files/2025-10/databricks-certified-machine-learning-professional-exam-guide-september.pdf
- Duration · https://www.databricks.com/sites/default/files/2025-10/databricks-certified-machine-learning-professional-exam-guide-september.pdf
- Official program page · https://www.databricks.com/sites/default/files/2025-10/databricks-certified-machine-learning-professional-exam-guide-september.pdf
NVIDIA-Certified Professional: AI Infrastructure (NCP-AII)
The NVIDIA-Certified Professional: AI Infrastructure (NCP-AII) is an intermediate-level credential for data center, infrastructure, network, storage, and system administrators, as well as solution architects. It validates the candidate's ability to deploy, configure, and troubleshoot NVIDIA AI infrastructure. To earn the credential, individuals must pass an online, remotely proctored exam hosted on Certiverse. The exam costs USD 400 and has a 120-minute time limit. Prerequisites include two to three years of operational experience deploying infrastructure for AI workloads using NVIDIA hardware. The certification remains valid for two years from issuance, with recertification requiring candidates to retake the exam. Successful participants receive a digital badge and an optional certificate.
- Price
- USD 400USD 400 for one exam attempt, normalized from the dollar amount on NVIDIA's official US page; preparation and repeat attempts are separate.
- Duration
- 120 minutes for the exam assessmentnot preparation time
- Level
- Professional
- Format
- Online, remotely proctored certification examQuestions: approximately 70 in the overview; 70–75 in the details table.
- Credential
- NVIDIA Certification
- Prerequisites
- Two to three years of operational experience working in a data center with NVIDIA hardware solutions. The candidate should be able to deploy all the parts of a data center infrastructure in support of AI workloads.
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-professional/
- Duration · https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-professional/
- Official program page · https://www.nvidia.com/en-us/learn/certification/ai-infrastructure-professional/
- Cost terms · https://www.nvidia.com/en-us/learn/certification/
NVIDIA-Certified Professional: AI Operations (NCP-AIO)
The NVIDIA-Certified Professional: AI Operations (NCP-AIO) is an intermediate-level certification designed for MLOps, DevOps, and AI infrastructure engineers. It validates the ability to monitor, troubleshoot, and optimize NVIDIA AI infrastructure. The certification costs USD 500 and consists of a 120-minute, remotely proctored online exam. The exam requires candidates to answer 30 multiple-choice questions and complete three hands-on lab exercises within the same single session. Prerequisites include two to three years of operational experience in a data center environment managing NVIDIA hardware. The credential is valid for two years, after which recertification requires retaking the exam. Candidates who pass receive a digital badge and an optional certificate. Topics evaluated include installation, deployment, administration, workload management, and troubleshooting using Slurm, Kubernetes, and Base Command Manager.
- Price
- USD 500USD 500 for one exam attempt, normalized from the dollar amount on NVIDIA's official US page; preparation and repeat attempts are separate.
- Duration
- 120 minutes for the exam assessmentnot preparation time
- Level
- Professional
- Format
- Online, remotely proctored certification exam with 30 multiple-choice questions and 3 hands-on labsQuestions: 30.
- Credential
- NVIDIA Certification
- Prerequisites
- Two to three years of operational experience working in a data center with NVIDIA hardware solutions. The candidate should be able to monitor and manage all the parts of a data center infrastructure in support of AI workloads.
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/ai-operations-professional/
- Duration · https://www.nvidia.com/en-us/learn/certification/ai-operations-professional/
- Official program page · https://www.nvidia.com/en-us/learn/certification/ai-operations-professional/
- Cost terms · https://www.nvidia.com/en-us/learn/certification/
NVIDIA-Certified Professional: AI Networking (NCP-AIN)
The NVIDIA-Certified Professional: AI Networking credential assesses intermediate ability to deploy and configure environments using NVIDIA networking technologies. NVIDIA lists a remotely proctored online exam with 70-75 questions, a 120-minute sitting time, English delivery and a USD 400 price on the reviewed US page. Candidates should have two to three years of NVIDIA data-center operational experience and be able to deploy and manage networking infrastructure for AI workloads. The blueprint covers Spectrum and InfiniBand networking, troubleshooting, automation, Kubernetes integration and AI data-center design. Passing participants receive a digital badge and optional certificate. The certification is valid for two years from issuance, and recertification may be achieved by retaking the exam. Optional preparation courses are listed separately.
- Price
- USD 400USD 400 for one exam attempt, normalized from the dollar amount on NVIDIA's official US page; preparation and repeat attempts are separate.
- Duration
- 120 minutes for the exam assessmentnot preparation time
- Level
- Professional
- Format
- Online, remotely proctored certification examQuestions: 70-75.
- Credential
- NVIDIA Certification
- Prerequisites
- Two to three years of operational experience working in a data center with NVIDIA hardware solutions. The candidate should be able to deploy and manage NVIDIA AI networking infrastructure in support of AI workloads.
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/ai-networking-professional/
- Duration · https://www.nvidia.com/en-us/learn/certification/ai-networking-professional/
- Official program page · https://www.nvidia.com/en-us/learn/certification/ai-networking-professional/
- Cost terms · https://www.nvidia.com/en-us/learn/certification/
NVIDIA-Certified Associate: Accelerated Data Science (NCA-ADS)
The NVIDIA-Certified Associate: Accelerated Data Science credential assesses entry-level proficiency with GPU-accelerated tools and libraries for data-science workflows. NVIDIA lists an online, remotely proctored exam with 50-60 questions, a 60-minute sitting time, English delivery and a USD 125 price on the reviewed US page. The page lists one to two years of accelerated data-science experience under prerequisites. Topics include data preparation, RAPIDS machine learning, pipelines, descriptive analysis, accelerated-data-science foundations, introductory MLOps, advanced data structures, and environment management. Passing participants receive a digital badge and optional certificate. The certification is valid for two years, and recertification may be achieved by retaking the exam. NVIDIA lists optional preparation resources but does not publish preparation hours.
- Price
- USD 125USD 125 for one exam attempt, normalized from the dollar amount on NVIDIA's official US page; preparation and repeat attempts are separate.
- Duration
- 60 minutes for the exam assessmentnot preparation time
- Level
- Associate
- Format
- Online, remotely proctored certification examQuestions: 50–60.
- Credential
- NVIDIA Certification
- Prerequisites
- 1–2 years of experience in accelerated data science, using GPU-based tools to efficiently process and analyze large datasets and improve the performance of machine learning, ETL, and analytics workloads.
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/accelerated-data-science-associate/
- Duration · https://www.nvidia.com/en-us/learn/certification/accelerated-data-science-associate/
- Official program page · https://www.nvidia.com/en-us/learn/certification/accelerated-data-science-associate/
- Cost terms · https://www.nvidia.com/en-us/learn/certification/
NVIDIA-Certified Professional: Accelerated Data Science (NCP-ADS)
The NVIDIA-Certified Professional: Accelerated Data Science credential assesses intermediate GPU-accelerated data-science workflows. The exam contains 60-70 questions, is listed in English and costs USD 200 on the reviewed US page. NVIDIA lists two to three years of hands-on accelerated data-science experience plus machine-learning, GPU-computing, optimization and end-to-end workflow foundations as prerequisites. Passing yields a digital badge and optional certificate. The certification is valid for two years; recertification may be achieved by retaking the exam. Preparation resources are optional, and no preparation-duration estimate is published.
- Price
- USD 200USD 200 for one exam attempt, normalized from the dollar amount on NVIDIA's official US page; preparation and repeat attempts are separate.
- Duration
- 120 minutes for the exam assessmentnot preparation time
- Level
- Professional
- Format
- Online, remotely proctored certification examQuestions: 60–70.
- Credential
- NVIDIA Certification
- Prerequisites
- Two to three years of hands-on experience in accelerated data science; Strong foundation in machine learning and GPU-accelerated computing; Experience in GPU-based optimization strategies and accelerated data manipulation techniques; Deep understanding of end-to-end data science workflows, from data preparation and cleansing to model development and deployment, with a focus on leveraging GPU acceleration for enhanced performance and efficiency
Sources ↗
- Price · https://www.nvidia.com/en-us/learn/certification/accelerated-data-science-professional/
- Duration · https://www.nvidia.com/en-us/learn/certification/accelerated-data-science-professional/
- Official program page · https://www.nvidia.com/en-us/learn/certification/accelerated-data-science-professional/
- Cost terms · https://www.nvidia.com/en-us/learn/certification/
AWS Certified AI Business Strategist (AIB-C01 beta)
AWS Certified AI Business Strategist (AIB-C01 beta) assesses AI investment evaluation, business cases, governance and scaling adoption; AWS says it does not assess AWS services knowledge. AWS announced beta registration from September 1, 2026 and exam delivery from September 29; on October 4 the page lists the beta exam with scheduling open. The main page lists 85 multiple-choice and multiple-response questions, USD 50 beta pricing and a future USD 100 standard price. English and Japanese are listed, with Pearson test-center or online-proctored delivery. No coding, AWS implementation experience or prior AWS certification is required; six months around AI initiatives is recommended.
- Price
- USD 50USD 50 beta exam price; AWS lists USD 100 as the standard exam price. Preparation and repeat attempts are separate.
- Duration
- 170-minute scheduled appointment on the certification pagethe exam guide separately states 130 minutes to complete the exam; neither is preparation time
- Level
- Business
- Format
- Beta certification examPearson test center or online proctored Questions: 85.
- Credential
- AWS Certification
- Prerequisites
- No mandatory coding, AWS implementation experience or prior AWS certification; AWS recommends basic AI familiarity and about six months working with or alongside AI initiatives.
Sources ↗
- Price : https://aws.amazon.com/certification/certified-ai-business-strategist/
- Duration : https://aws.amazon.com/certification/certified-ai-business-strategist/
- Official program page : https://aws.amazon.com/certification/certified-ai-business-strategist/
- Modules or exam domains : https://docs.aws.amazon.com/aws-certification/latest/ai-business-strategist-01/ai-business-strategist-01.html
- Credential details : https://aws.amazon.com/certification/recertification/
- Credential details : https://aws.amazon.com/certification/faqs/
- Credential details : https://www.credly.com/org/amazon-web-services/badge/aws-certified-ai-business-strategist
Google AI Professional Certificate
The Google AI Professional Certificate is an online, self-paced beginner program consisting of eight courses focused on workplace AI fluency. Learners complete over twenty hands-on activities covering brainstorming, data analysis, content creation, and application development without writing code. Topics include prompting, responsible AI use, and building custom tools using vibe coding. No prior programming or AI experience is required. Learners can use browser-based generative AI tools for labs. US access costs USD 49 per month; financial aid is available. Completing all eight courses earns a shareable certificate from Google. This is workplace AI practice, rather than advanced machine-learning programming instruction.
- Price
- Google AI Professional Certificate · USD 49 / month regularNo promotional price stated.
Region, access and offer terms
US price; prices may vary in other countries. No Canadian currency inference.
No promotional price stated in the checked source.
Program-specific subscription includes all eight courses and graded assessments. This is access pricing, not a completion total. Google AI Pro trial is optional and subject to terms; financial-aid recipients do not receive that trial. In the U.S. and Canada, the subscription cost is $49 per month. When you purchase the Google AI Professional Certificate, you’ll have access to all course materials, including videos, activities, readings, and graded assessments.
- Duration
- 8 hours (top-level estimate)separate module estimates total 13 hours.
- Level
- Beginner
- Format
- Online, self-paced
- Credential
- Course completion certificate
- Prerequisites
- No prerequisites; no previous AI or coding experience required.
Sources ↗
- Price · https://www.coursera.org/professional-certificates/google-ai
- Duration · https://www.coursera.org/professional-certificates/google-ai
- Official program page · https://www.coursera.org/professional-certificates/google-ai
- Provider subscription terms · https://www.coursera.org/professional-certificates/google-ai
AI Business Fundamentals
AI Business Fundamentals is a 10-hour online self-paced learning track offered by DataCamp. The program consists of six courses focusing on the integration of artificial intelligence into professional environments. Learners explore topics such as generative AI, large language models, AI ethics, and the development of scalable AI strategies. The curriculum focuses on theory and business implementation, rather than coding. It is intended for professionals with prior AI knowledge. Access to the full track requires a DataCamp Premium subscription, which costs USD 35 per month, covering access rather than a guaranteed total cost to finish. Upon finishing all six courses, learners earn a Statement of Accomplishment that can be shared on professional profiles.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 10 hours
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
AI Agent Fundamentals
DataCamp AI Agent Fundamentals is a self-paced online skill track consisting of three courses. The program covers the foundational concepts of AI agents, their practical frameworks like the Thought-Action-Observation loop, and their real-world applications. Learners explore components necessary for building scalable agentic systems, including the Model Context Protocol and Agent-to-Agent protocol. The track is estimated by the provider to take six hours to complete. Access requires a DataCamp Premium subscription, which is priced at USD 35 for a regular one-month period. This covers access, not guaranteed completion. The theory track suits conceptual learning rather than coding practice. There are no prerequisites. Upon finishing the three courses, learners earn a Statement of Accomplishment issued by DataCamp.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 6 hours
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Machine Learning Fundamentals in Python
DataCamp provides the Machine Learning Fundamentals in Python learning track as an online, self-paced program. The curriculum consists of four courses, beginning with supervised learning using the scikit-learn library and progressing through unsupervised learning techniques. You subsequently study deep learning with PyTorch, which involves constructing a neural network from scratch, and conclude with reinforcement learning utilizing the Gymnasium library. In addition to the four courses, the track incorporates three bonus projects and one bonus skill assessment. Access requires a Premium subscription, which is priced at USD 35 for a regular one-month period. This beginner track lists no prerequisites and focuses on Python rather than R. Upon completing the track, you earn a Statement of Accomplishment from DataCamp.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 16 hours
- Level
- Beginner
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/machine-learning-fundamentals-with-python
- Official program page · https://www.datacamp.com/tracks/machine-learning-fundamentals-with-python
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
Deep Learning in Python
The Deep Learning in Python track by DataCamp is an eighteen-hour online, self-paced learning program designed for beginners who are already familiar with traditional machine learning. Accessible through a DataCamp Premium subscription starting at USD 35 per month, the curriculum teaches students how to build and train neural networks using the PyTorch framework. The track consists of five courses and one bonus project, covering topics such as image classification, time series prediction, natural language processing, and the Transformers architecture. Upon finishing the required materials, learners receive a Statement of Accomplishment that can be shared on professional profiles. This monthly subscription grants platform access rather than representing a fixed, guaranteed total cost to complete the program.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 18 hours
- Level
- Beginner
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Developing Applications with LangChain
DataCamp’s Developing Applications with LangChain is an online, self-paced learning track focused on building large language model applications using Python. The program consists of three courses covering core application development, Retrieval Augmented Generation, and the design of agentic systems, alongside a bonus project on building chatbots for technical documentation. The provider estimates the track requires approximately nine hours to complete, and there are no stated prerequisites to enroll. Access requires a DataCamp Premium subscription, which costs USD 35 for one month of regular access; this covers access, not guaranteed completion. The track suits Python-focused development rather than other programming languages. Upon finishing the track, learners receive a Statement of Accomplishment that can be shared on professional profiles.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 9 hours
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/developing-applications-with-langchain
- Official program page · https://www.datacamp.com/tracks/developing-applications-with-langchain
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
Developing AI Applications
Developing AI Applications is a 21-hour, self-paced online learning track offered by DataCamp. It is designed to teach learners how to create artificial intelligence systems and applications using current developer tools. The curriculum consists of eight courses and two bonus projects, covering topics such as prompt engineering, large language models, AI ethics, and data privacy. Throughout the track, you will work with the OpenAI API, Hugging Face, and LangChain to build chatbots, text analysis tools, and recommendation engines. Access requires a DataCamp Premium subscription, which costs USD 35 per month, covering access rather than guaranteed completion. The track has no prerequisites. Track completion earns a Statement of Accomplishment. This route suits Python application practice rather than an exam-certification goal.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 21 hours
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Machine Learning Scientist in Python
The Machine Learning Scientist in Python track by DataCamp is an online program with 85 listed hours covering supervised, unsupervised, and deep learning. Designed for aspiring machine learning scientists, it introduces Python programming concepts using real-world datasets. The curriculum features 21 interactive courses covering topics like scikit-learn, XGBoost, natural language processing with spaCy, and deep learning with PyTorch. Learners explore feature engineering, time series data, and encounter three bonus projects and one bonus skill assessment. DataCamp states there are no prerequisites, making it suitable for beginners. Access requires a Premium subscription at USD 35 per month regular, which is not a guaranteed total completion cost. Upon finishing the 21 courses, learners earn a Statement of Accomplishment.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 85 hours
- Level
- Beginner
- Format
- Online track with interactive courses, projects and a bonus skill assessment
- Credential
- Statement of Accomplishment
- Prerequisites
- The prerequisite panel says no prerequisites; the FAQ says suitable for beginners.
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/machine-learning-scientist-with-python
- Official program page · https://www.datacamp.com/tracks/machine-learning-scientist-with-python
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
Machine Learning Engineer
DataCamp offers the Machine Learning Engineer track, an online program designed to prepare aspiring professionals for junior roles in deployment, operations, monitoring, and maintenance. Through interactive courses, you learn to design, train, and deploy end-to-end models using technologies like Python, Docker, and MLflow. The curriculum covers MLOps concepts, CI/CD pipelines, data quality, and model monitoring to address data and concept drift. Access requires a Premium subscription, available for USD 35 per month regular, which provides access to the learning materials but does not guarantee a total completion cost. Upon finishing the program, you earn a Statement of Accomplishment. Prior knowledge of data manipulation and machine learning model training and evaluation using Python is expected.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 44 hours
- Format
- Online track with interactive courses, projects and a bonus skill assessment
- Credential
- Statement of Accomplishment
- Prerequisites
- Program description and beginner FAQ expect prior Python data manipulation and machine-learning model training/evaluation. Generic prerequisites panel contradicts this by saying none.
Sources ↗
ChatGPT Fundamentals
ChatGPT Fundamentals is a self-paced online learning track with three listed hours offered by DataCamp. Designed to introduce the basics of ChatGPT and prompt engineering, the program consists of three specific courses: Understanding ChatGPT, Understanding Prompt Engineering, and Intermediate ChatGPT. Learners access the content through a DataCamp Premium subscription, which costs USD 35 for one month of regular access. There are no prerequisites required to begin this foundational track. Throughout the curriculum, participants explore ChatGPT's architecture, learn prompt crafting techniques, and engage with bonus resources covering custom models and advanced data analysis. Upon finishing the three courses, students receive a Statement of Accomplishment from DataCamp, which can be shared on professional networks and resumes.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 3 hours
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Natural Language Processing in Python
DataCamp provides an online, self-paced learning track titled Natural Language Processing in Python. Designed for beginners with no stated prerequisites, the program lists 20 hours of content. The curriculum consists of five courses covering text analysis, sentiment analysis, spaCy, spoken language processing, and feature engineering, plus one bonus project. Learners use Python libraries like NLTK, scikit-learn, spaCy, and SpeechRecognition to extract insights from unstructured data, including text and audio. Access requires a DataCamp Premium subscription, available for USD 35 per month regular. Because this fee is for monthly access, the total amount depends on the subscription route and billing periods selected. Upon finishing, participants receive a Statement of Accomplishment.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 20 hours
- Level
- Beginner
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/natural-language-processing-in-python
- Official program page · https://www.datacamp.com/tracks/natural-language-processing-in-python
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
Developing Large Language Models
The "Developing Large Language Models" track by DataCamp is a self-paced online program focused on deep learning and natural language processing using Python, PyTorch, and Hugging Face. The curriculum comprises seven courses and two bonus projects, covering introductory concepts through to advanced applications like Llama 3 integration, transformer architectures, and reinforcement learning from human feedback. DataCamp lists 19 hours of content. Access to the full learning track is available through a DataCamp Premium subscription, which costs USD 35 per month regular. The prerequisites panel states no prerequisites. Upon completing the track, participants receive a Statement of Accomplishment, which they can add to their resume or social media profiles.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 19 hours
- Format
- Online self-paced learning track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
MLOps Fundamentals
The DataCamp MLOps Fundamentals track is a conceptual program with 14 listed hours consisting of four courses focused on productionizing and monitoring machine learning models. The curriculum covers MLOps concepts, developing models for production, deployment and life cycling, and fully automated MLOps architectures. Access requires a DataCamp Premium subscription, priced at USD 35 per month at the regular price checked on 8 September 2026. The track does not teach a specific programming language, focusing instead on theoretical frameworks such as continuous integration, continuous deployment, and model registries. Throughout the track, learners study the complete lifecycle of a machine learning application. Upon finishing the four modules, learners receive a DataCamp Statement of Accomplishment.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 14 hoursProvider-listed track duration; not a guaranteed elapsed completion time.
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- The prerequisites panel states no prerequisites. The FAQ states that prior knowledge of machine learning and Python is assumed and that this track is not suitable for beginners.
Sources ↗
Machine Learning in Production in Python
The Machine Learning in Production in Python skill track is offered by DataCamp for aspiring data scientists and machine learning engineers. Access to this program requires a Premium subscription, which is priced at USD 35 per month at the regular price checked on 8 September 2026. The track consists of five courses and one bonus project, with a provider-listed duration of nineteen hours. The curriculum covers MLOps concepts, MLflow, machine learning monitoring, and data versioning using Data Version Control. The listed sequence starts with MLOps Concepts and ends with Introduction to Data Versioning with DVC. The provider states there are no prerequisites for this track. Upon finishing the five courses, learners earn a Statement of Accomplishment.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 19 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Supervised Machine Learning in R
DataCamp offers the Supervised Machine Learning in R track, a beginner-level program with 25 listed hours focused on teaching predictive modeling and evaluation using the Tidyverse ecosystem. The curriculum consists of six courses, covering topics such as multiple and logistic regression, tree-based models, support vector machines, and hyperparameter tuning, alongside one bonus project assessing medical treatments. Upon finishing the courses, learners receive a Statement of Accomplishment. DataCamp lists no prerequisites for this track. Access to the program requires a Premium subscription, which costs USD 35 per month at the regular price checked on 8 September 2026. This subscription fee provides one month of access and does not represent a guaranteed total cost for completion.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 25 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Machine Learning Fundamentals in R
Machine Learning Fundamentals in R is a beginner-level educational track offered by DataCamp. The curriculum has 24 provider-listed hours, consisting of six specific courses covering classification, regression, unsupervised learning, and R packages like caret and tidymodels. The program also features one bonus project and a bonus skill assessment. Access requires a Premium subscription, priced at USD 35 per month regular as of September 8, 2026, which is an access price rather than a guaranteed completion cost. Upon finishing the six core courses, learners receive a Statement of Accomplishment. The provider states there are no prerequisites. This track is designed for individuals seeking introductory knowledge for roles such as data scientist or artificial intelligence specialist.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 24 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Machine Learning Scientist in R
The Machine Learning Scientist in R track by DataCamp is a self-paced track with 65 listed hours and sixteen courses. Learners access the curriculum through a Premium subscription, priced at USD 35 per month at the regular price checked on 8 September 2026. The program focuses on applying R programming to supervised and unsupervised machine learning workflows. Participants receive a Statement of Accomplishment upon completion. The curriculum covers classification, regression, feature engineering, clustering, dimensionality reduction, and Bayesian data analysis using tidymodels and other R packages. The provider includes two bonus items: a skill assessment and a project on predicting movie rental durations. The stated subscription price represents one month of access and does not guarantee a total completion cost.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 65 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- The panel states no prerequisites. The beginner FAQ expects R programming and basic machine-learning concepts and recommends mathematics. Another FAQ says prior machine-learning knowledge is not necessary but says the track is best suited to basic R and machine-learning familiarity.
Sources ↗
Image Processing in Python
Image Processing in Python is a beginner-level track offered by DataCamp that has 12 provider-listed hours. The curriculum covers image pre-processing, restoration, and deep learning using Python. Learners progress through three courses: Image Processing in Python, Biomedical Image Analysis in Python, and Image Modeling with Keras. There are no prerequisites for enrollment. DataCamp issues a Statement of Accomplishment upon finishing the track, which serves as a completion record rather than a formal certification. Access requires a monthly Premium subscription, priced at USD 35 at the regular price checked on 8 September 2026. This price reflects one month of access, not a guaranteed total cost to finish the entire learning path. The program includes one bonus project about object detection.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 12 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Keras Fundamentals
The DataCamp Keras Fundamentals track is a beginner-level track designed for software engineers, data scientists, researchers, and developers seeking deep-learning skills. With 16 provider-listed hours, the curriculum consists of four courses and one bonus project. Learners explore deep learning, image modeling, and recurrent neural networks using Python. There are no prerequisites required to begin. DataCamp provides access to this track through a Premium monthly subscription, priced at USD 35 at the regular price checked on 8 September 2026, which represents one month of access rather than a guaranteed total completion cost. Upon finishing the track, learners receive a Statement of Accomplishment that can be shared on professional networks and resumes.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 16 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track.
Sources ↗
Time Series in Python
DataCamp offers the Time Series in Python track, a beginner-level program for data scientists, data engineers, data analysts, and software developers seeking time-series experience. The curriculum has a provider-listed duration of approximately 20 hours. There are no prerequisites. The program consists of five courses and one bonus project, teaching learners to manipulate time-series data using pandas, analyze it with NumPy and statsmodels, and forecast using ARIMA and machine-learning models. Access requires a Premium subscription, which at the regular price checked on 8 September 2026 costs USD 35 for one month; this reflects the monthly rate and not a guaranteed total cost to finish. Graduates earn a Statement of Accomplishment.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 20 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track.
Sources ↗
Supervised Machine Learning in Python
DataCamp offers the Supervised Machine Learning in Python track, a beginner-level program with 25 provider-listed hours. Access requires a Premium subscription, priced at USD 35 per month regular, checked 8 September 2026, which represents one month of access and not a guaranteed total completion cost. The curriculum consists of six courses covering prediction using labeled data, including linear and logistic regression, Support Vector Machines, and tree-based models in scikit-learn, as well as Extreme Gradient Boosting with XGBoost, hyperparameter tuning, and ensemble learning. The track also includes two separate bonus projects. There are no prerequisites for this track. Upon finishing the modules, learners receive a Statement of Accomplishment from DataCamp.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 25 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track.
Sources ↗
- Price · https://www.datacamp.com/pricing?period=monthly
- Duration · https://www.datacamp.com/tracks/supervised-machine-learning-in-python
- Official program page · https://www.datacamp.com/tracks/supervised-machine-learning-in-python
- Provider subscription terms · https://www.datacamp.com/pricing?period=monthly
OpenAI Fundamentals
DataCamp offers the OpenAI Fundamentals skill track, a beginner-level program designed for building artificial intelligence systems using OpenAI frontier models. With 15 provider-listed hours, the curriculum consists of five primary courses and two separate bonus items. Topics include working with the OpenAI API, multi-modal systems, prompt engineering, the OpenAI Responses API, and embeddings. The track requires no prior experience with artificial intelligence or Python. Access is provided through the DataCamp Premium subscription, priced at USD 35 per month at the regular price checked on 8 September 2026. This subscription provides one month of access and does not guarantee total completion cost. Upon completion, learners receive a Statement of Accomplishment.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 15 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Level
- Beginner
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
Intro to AI Agents and Agentic AI
"Intro to AI Agents and Agentic AI" is a basic-level, online self-paced course offered by 365 Data Science. It focuses on the fundamentals of artificial intelligence agents, different agent architectures, and practical implementation using tools like n8n. The curriculum consists of two hours of advertised content alongside fifty-two lessons and twenty-eight exercises, with a separately listed sixty-minute course exam. The provider lists "Intro to AI" as the prerequisite course. Access to the program is provided through the provider's Self-Study subscription plan, which costs USD 36 per month regular. The course advertises three CPE credits in Specialized Knowledge.
- Price
- 365 Data Science Self-Study · USD 36/month for course content, billed monthly at the regular price. (see provider page)
USD price displayed on the official English pricing page, checked 9 September 2026; regional checkout pricing and taxes are not established. · Official pricing - Duration
- 2 hoursOfficial course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026.
- Level
- Basic
- Format
- Online self-paced course
- Credential
- Course certificate
- Prerequisites
- Intro to AI course
Sources ↗
AI Agent Architecture
The AI Agent Architecture course by 365 Data Science is an intermediate, online self-paced program focused on building agentic systems. The curriculum features two hours of advertised content across twelve instructional modules, with a separately listed sixty-minute exam. Learners explore single and multi-agent structures, prompting frameworks, planning, execution, and memory systems. Covered methodologies include ReAct, ReWOO, and prompt chaining. Prerequisites are introductory courses in AI and AI agents. Course access requires a Self-Study subscription, priced at USD 36 per month regular. The course advertises four CPE credits. This subscription provides one month of access to the provider's learning platform, rather than a fixed cost for guaranteed program completion.
- Price
- 365 Data Science Self-Study · USD 36/month for course content, billed monthly at the regular price. (see provider page)
USD price displayed on the official English pricing page, checked 9 September 2026; regional checkout pricing and taxes are not established. · Official pricing - Duration
- 2 hoursOfficial course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026.
- Level
- Intermediate
- Format
- Online self-paced course
- Credential
- Course certificate
- Prerequisites
- Intro to AI; Intro to AI agents
Sources ↗
Hugging Face Fundamentals
The Hugging Face Fundamentals track by DataCamp is a track with twelve provider-listed hours covering open-source artificial intelligence models. The curriculum consists of four courses, starting with the Hugging Face Hub and transformers library before progressing to large language models in Python. Learners study multi-modal models for text, image, audio, and video generation, and conclude by building AI agents with the smolagents framework. A separate bonus project on food image classification is also included. The track requires no prerequisites and is accessible through a DataCamp Premium subscription for USD 35 per month regular. Upon finishing the four courses, participants earn a Statement of Accomplishment. The access price is not a guaranteed completion cost.
- Price
- DataCamp Premium · USD 35/month for course content, billed monthly at the regular price. (see provider page)
Premium for Individuals. English public pages with USD explicitly selected; visitor country not stated. Monthly regular access observed 2026-09-08 was USD 35. Annual regular access observed 2026-09-05 was USD 330, billed annually; a time-limited promotion was displayed on 5 September 2026. Access price is not a guarantee of track completion. · Official pricing - Duration
- 12 hoursProvider-listed track duration; not guaranteed elapsed completion time.
- Format
- Track
- Credential
- Statement of Accomplishment
- Prerequisites
- There are no prerequisites for this track
Sources ↗
AI Agents in Practice
"AI Agents in Practice" is an online, self-paced course by 365 Data Science focused on designing agentic systems. Billed as an advanced-level program, the curriculum contains two hours of advertised content. Learners access the materials via the provider's Self-Study subscription for USD 36 per month regular. Additional third-party costs for OpenAI API usage may apply during practical exercises. The syllabus covers core agent principles, prompt techniques, and frameworks such as ReAct, ReWOO, LangGraph, and LangSmith. The curriculum includes three taught project walkthroughs and a separate final project-and-exam section. The listed prerequisites are intermediate Python skills and a basic understanding of large language models and prompt design.
- Price
- 365 Data Science Self-Study · USD 36/month for course content, billed monthly at the regular price. (see provider page)
USD price displayed on the official English pricing page, checked 9 September 2026; regional checkout pricing and taxes are not established. · Official pricing - Duration
- 2 hoursOfficial course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026.
- Level
- Advanced
- Format
- Online self-paced course
- Credential
- Course certificate
- Prerequisites
- Intermediate Python skills (comfort with functions, basic data structures, and working in notebooks); Basic familiarity with large language models (e.g., using ChatGPT, prompts, tokens, system vs user messages); A general understanding of AI concepts is helpful but not required
Sources ↗
Evaluating AI Agents: From Metrics to Real-World Impact
Evaluating AI Agents: From Metrics to Real-World Impact is an intermediate, online self-paced course offered by 365 Data Science. Designed for artificial intelligence developers, product managers, and researchers, the curriculum covers quantitative and qualitative approaches to assessing models. Learners examine generative systems, classifiers, and retrieval-augmented generation pipelines across two advertised hours of content. The program explores evaluation metrics such as Goal Success Rate, Context Recall, precision, recall, and F1-scores, alongside human-centric feedback and ethical considerations like bias and hallucination mitigation. Prospective students need a working knowledge of Python and a basic understanding of machine learning workflows. Access to the material, the capstone project, and the concluding forty-minute examination requires a Self-Study subscription, which costs USD 36 per month regular.
- Price
- 365 Data Science Self-Study · USD 36/month for course content, billed monthly at the regular price. (see provider page)
USD price displayed on the official English pricing page, checked 9 September 2026; regional checkout pricing and taxes are not established. · Official pricing - Duration
- 2 hoursOfficial course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026.
- Level
- Intermediate
- Format
- Online self-paced course
- Credential
- Course certificate
- Prerequisites
- Working knowledge of Python (functions, dictionaries, basic libraries like pandas); Basic understanding of machine learning workflows; No prior experience with AI evaluation frameworks needed
Sources ↗
- Price · https://365datascience.com/pricing/
- Duration · https://365datascience.com/courses/evaluating-ai-agents-from-metrics-to-real-world-impact/
- Official program page · https://365datascience.com/courses/evaluating-ai-agents-from-metrics-to-real-world-impact/
- Provider subscription terms · https://365datascience.com/pricing/
Build Conversational AI Memory with LangGraph
365 Data Science offers the advanced online self-paced course "Build Conversational AI Memory with LangGraph." Access requires a Self-Study subscription for USD 36 per month regular; third-party API usage may cost extra. The curriculum provides two advertised hours of instructional content across six subject modules, starting with an introduction and environment setup before covering graph components, message management, and thread-level persistence. Learners finish with a combined course project and exam section listed at 160 minutes. The program features 21 lessons, three exercises, one project, and two exams. Intermediate Python skills are required, and LangChain familiarity is recommended.
- Price
- 365 Data Science Self-Study · USD 36/month for course content, billed monthly at the regular price. (see provider page)
USD price displayed on the official English pricing page, checked 9 September 2026; regional checkout pricing and taxes are not established. · Official pricing - Duration
- 2 hoursOfficial course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026.
- Level
- Advanced
- Format
- Online self-paced course
- Credential
- Course certificate
- Prerequisites
- Python (version 3.8 or later), LangGraph and LangChain libraries, OpenAI API key, and a code editor or IDE (e.g., VS Code or Jupyter Notebook); Intermediate Python skills are required. Familiarity with LangChain and basic concepts in AI agents or conversational systems is recommended.
Sources ↗
- Price · https://365datascience.com/pricing/
- Duration · https://365datascience.com/courses/build-conversational-ai-memory-with-langgraph/
- Official program page · https://365datascience.com/courses/build-conversational-ai-memory-with-langgraph/
- Provider subscription terms · https://365datascience.com/pricing/
Introduction to Vector Databases with Pinecone
The Introduction to Vector Databases with Pinecone is an advanced, online self-paced course provided by 365 Data Science. The program contains two advertised hours of instructional content and a separately listed thirty-minute course exam. Learners access the materials through the 365 Data Science Self-Study subscription plan, which costs USD 36 per month regular for access. The curriculum covers vector spaces, embedding algorithms, and the practical implementation of semantic search engines using Python and Pinecone. Prerequisites include intermediate Python skills, a Pinecone account with an active API key, and a compatible code editor such as Jupyter Notebook. The coursework culminates in a case study where learners apply their knowledge to custom data.
- Price
- 365 Data Science Self-Study · USD 36/month for course content, billed monthly at the regular price. (see provider page)
USD price displayed on the official English pricing page, checked 9 September 2026; regional checkout pricing and taxes are not established. · Official pricing - Duration
- 2 hoursOfficial course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026.
- Level
- Advanced
- Format
- Online self-paced course
- Credential
- Course certificate
- Prerequisites
- Python (version 3.8 or later), Pinecone account and API key, and a code editor or IDE (e.g., VS Code or Jupyter Notebook); Intermediate Python skills are required. Familiarity with embeddings, APIs, or LangChain is helpful but not mandatory.
Sources ↗
- Price · https://365datascience.com/pricing/
- Duration · https://365datascience.com/courses/introduction-to-vector-databases-with-pinecone/
- Official program page · https://365datascience.com/courses/introduction-to-vector-databases-with-pinecone/
- Provider subscription terms · https://365datascience.com/pricing/
Introduction to AI
The Introduction to AI course, created by MinnaLearn and the University of Helsinki, is a free, self-paced online program exploring artificial intelligence fundamentals. The curriculum contains six chapters covering AI definitions, problem solving, probability applications, machine learning types, neural networks, and societal implications. Designed for a general audience with no complicated math or programming prerequisites, the course requires participants to complete at least ninety percent of the exercises with a minimum fifty percent accuracy rate. Assessment includes peer-evaluated exercises requiring learners to provide and receive peer reviews. Upon meeting these requirements, participants earn a digital Elements of AI: Introduction to AI certificate at no cost, which can be shared via URL on LinkedIn.
- Price
- FreeCourse access and the certificate are free.
- Duration
- Approximately 4–8 hours per partprovider recommends finishing in 6 weeks, self-paced.
- Format
- Free online courseself-paced
- Credential
- Certificate
- Prerequisites
- No complicated math or programming required
Sources ↗
- Price · https://www.elementsofai.com/faq/i-have-passed-an-elements-of-ai-course-where-is-my-certificate-2
- Duration · https://www.elementsofai.com/faq/how-many-hours-will-the-course-take
- Official program page · https://www.elementsofai.com/
- Modules or exam domains · https://course.elementsofai.com/
- Credential details · https://www.elementsofai.com/faq/how-to-share-your-certificate-in-linkedin
Building AI
Building AI is a flexible online course offered by the University of Helsinki and MinnaLearn that takes approximately 50 hours to complete. It explores the algorithms underlying artificial intelligence. The curriculum covers fundamental optimization, probability, machine learning, and neural networks. Learners can choose from beginner, intermediate, and advanced exercise options. The intermediate and advanced tiers require programming. While prior completion of Introduction to AI is recommended, it is not a prerequisite. All course content and exercises are accessible for free. Learners who complete 19 of 21 exercises with at least half correct can purchase an optional electronic certificate for EUR 50. The program ends with an optional AI idea project.
- Price
- FreeCourse content and all exercises at all levels are free; the optional certificate is not included. Optional upgrade adds EUR 50: Optional electronic certificate; excluded from free course access. EUR 50 including VAT if applicable; successful completion and purchase required.
- Duration
- Approximately 50 hours to complete the whole coursevaries by difficulty and optional project.
- Level
- Basic Understanding
- Format
- Flexible online course
- Credential
- Certificate
- Prerequisites
- Basic Python recommended; Introduction to AI recommended but not a prerequisite; intermediate and advanced exercises require programming.
Sources ↗
- Price · https://www.elementsofai.com/faq/what-are-the-requirements-for-completing-the-introduction-to-ai-and-building-ai-courses-2
- Duration · https://www.elementsofai.com/faq/how-many-hours-will-the-course-take
- Official program page · https://buildingai.elementsofai.com/
- Credential details · https://www.elementsofai.com/faq/how-to-share-your-certificate-in-linkedin
- Optional price component · https://www.elementsofai.com/faq/i-have-passed-an-elements-of-ai-course-where-is-my-certificate-2
Professional Certificate Program in Machine Learning & Artificial Intelligence
The Professional Certificate Program in Machine Learning and Artificial Intelligence is an On Campus and Live Online course-based program from MIT Professional Education. Learners complete at least 16 days of qualifying Short Programs courses within a 36-month window. The curriculum requires the Machine Learning for Big Data and Text Processing core courses; learners with prior experience may begin with the Advanced course, while others must take Foundations and Advanced. Participants then select electives covering topics like natural language processing, predictive analytics, deep learning algorithms, robotics, and large language model architecture. The credential requires full attendance for each selected course. Tuition is charged per selected course, in addition to a USD 325 non-refundable application fee.
- Duration
- At least 16 days of qualifying courses, completed within 36 months of the first qualifying course. Attend the full duration of each coursenot a 36-month instruction duration or guaranteed completion estimate.
- Format
- On Campus & Live Online course-based professional certificate program
- Credential
- Professional Certificate
- Prerequisites
- Core-course route depends on experience: prior machine-learning experience permits starting with Advanced; without relevant experience, take Foundations and Advanced. The stated three-year experience and technical bachelor's profile is under Who Should Attend, not independently stated as a universal admission requirement.
Sources ↗
Artificial Intelligence: Business Strategies and Applications
UC Berkeley Executive Education offers the online Artificial Intelligence: Business Strategies and Applications program for senior leaders, functional heads, and professionals exploring AI adoption. Over two months, learners allocate four to six hours weekly to study generative AI, prediction simulations, algorithmic bias, and organizational change. The curriculum includes four live sessions, subject to change, starting with current business applications and progressing through predictive models and team building, concluding with future AI trends. Participants engage with recorded materials, case studies featuring organizations like Vodafone, assignments, and discussions. The program requires a USD 3050 fee and culminates in a Capstone Business Challenge Project. Successful participants receive a digital Certificate of Completion, which does not confer degree credit.
- Price
- USD 3050Program fee. As shown in the United States on 7 October 2026, the official program page lists one online cohort, Nov 12, 2026 - Jan 28, 2027, at $3,050.00.
- Duration
- 2 months4–6 hours per week.
- Format
- Online learning programlive and recorded sessions
- Credential
- Certificate of Completion
- Prerequisites
- No technical background required.
Sources ↗
- Price · https://executive.berkeley.edu/programs/artificial-intelligence-business-strategies-and-applications
- Duration · https://executive.berkeley.edu/programs/artificial-intelligence-business-strategies-and-applications
- Official program page · https://executive.berkeley.edu/programs/artificial-intelligence-business-strategies-and-applications
Leadership Program in AI
As reviewed in the United States on 1 October 2026, Leadership Program in AI was Wharton Executive Education's six-month program for nontechnical senior executives. Applicants needed at least ten years of work experience; a coding background was not required. Self-paced online learning, faculty-led live sessions, and live webinars on generative AI covered data-driven decisions, machine learning, AI responsibilities, and organizational use of data and algorithms. A six-week leadership course and a capstone with six checkpoints were included. Successful completion earned a digital certificate, not a degree or earned academic credit. The optional two-day campus event was generally held six to nine months after completion. Programme price not stated for the United States on 25 September 2026 in the saved page text. The page describes instalment options; the optional on-campus event registration is USD 250, as shown in the United States on 25 September 2026. This is not the programme fee or an all-in total. Travel and accommodation are excluded.
- Duration
- 6 months15 weeks of core modules plus a six-week online leadership short course. Optional two-day event generally held six to nine months after program completion. Source disagreement on weekly hours as shown in the United States on 1 October 2026.Official source · Checked
- Format
- Self-paced online learning and faculty-led live sessionssix-week online leadership short course; optional two-day on-campus networking and recognition ceremony. The networking event is generally held within six to nine months from the date of completion of the program.Official source · Checked
- Credential
- Digital certificate of completionOfficial source · Checked
- Prerequisites
- A minimum of 10 years of work experience; no technical or coding background required.Official source · Checked
Sources ↗
Data Science with Python
Study statistical learning using Python, including tree-based methods, neural networks and clustering. The course links technical concepts to data-science practice and real-world applications. Its audience includes professionals moving into data science and IT practitioners. Mathematics, statistics and programming familiarity are recommendations, not presented as mandatory admission rules. Course delivery and the university credential are distinct from applying directly to the university.
- Price
- USD 660Price details observed 2026-10-11. Displayed programme fee on 11 October 2026, as shown in the United States; not a verified checkout total. A time-limited promotion was displayed on 11 October 2026.Official source · Checked ; Official source · Checked
- Duration
- 8 weeks excluding orientation7–10 hours per week.Official source · Checked
- Format
- Online cohort-based short courseself-paced study within the cohort.Official source · Checked
- Credential
- Certificate of completionOfficial source · Checked
- Prerequisites
- Fundamental mathematics and statistics, plus familiarity with at least one programming language, are recommended. These recommendations are not stated as mandatory admission requirements.Official source · Checked
Sources ↗
- Price : https://www.getsmarter.com/products/uct-data-science-with-python-online-short-course
- Duration : https://www.getsmarter.com/products/uct-data-science-with-python-online-short-course
- Official program page : https://www.getsmarter.com/products/uct-data-science-with-python-online-short-course
- Cost terms : https://www.getsmarter.com/terms-and-conditions-for-students
AI for Business: From Vision to Value
Explore AI adoption through business strategy, organizational readiness, governance, performance evaluation and project management. Global and African business examples accompany work on a tailored AI implementation plan. The intended audience includes midcareer and senior professionals who shape or support business strategy. Technical experience and coding proficiency are not required. The plan is coursework, not a promise of business results.
- Price
- USD 998Price details observed 2026-10-09. Displayed programme fee on 9 October 2026, as shown in the United States; not a verified checkout total. Terms source retains its separate 18 September observation date. A time-limited promotion was displayed on 9 October 2026; no promotional total is inferred. The final price requires checkout confirmation.Official source · Checked ; Official source · Checked
- Duration
- 6 weeks excluding orientation6–10 hours per week.Official source · Checked
- Format
- Online cohort-based short courseself-paced study within the cohort.Official source · Checked
- Credential
- Certificate of completionOfficial source · Checked
- Prerequisites
- No technical experience or coding proficiency required.Official source · Checked
Sources ↗
- Price · https://www.getsmarter.com/products/uct-ai-for-business-from-vision-to-value-online-short-course
- Duration · https://www.getsmarter.com/products/uct-ai-for-business-from-vision-to-value-online-short-course
- Official program page · https://www.getsmarter.com/products/uct-ai-for-business-from-vision-to-value-online-short-course
- Cost terms · https://www.getsmarter.com/terms-and-conditions-for-students
Oxford Artificial Intelligence Programme
Explore the AI ecosystem, machine learning, neural networks, generative AI and their societal and business implications. This nontechnical programme addresses business leaders as well as professionals working across technology and organizational decisions. Programming skills are not required. The programme page describes a certificate of attendance from Oxford Saïd, subject to the stated completion requirements; it is not described here as a degree or a completion certificate.
- Price
- USD 3237Price details observed 2026-10-09. Displayed programme fee on 9 October 2026, as shown in the United States; not a verified checkout total. Terms source retains its separate 18 September observation date. A time-limited promotion was displayed on 9 October 2026; no promotional total is inferred. The final price requires checkout confirmation.Official source · Checked ; Official source · Checked
- Duration
- 6 weeks excluding orientation7–10 hours per week.Official source · Checked
- Format
- Online cohort-based short courseself-paced study within the cohort.Official source · Checked
- Credential
- Certificate of attendanceOfficial source · Checked
- Prerequisites
- No programming skills needed; the programme is framed as nontechnical.Official source · Checked
Sources ↗
- Price · https://www.getsmarter.com/products/oxford-artificial-intelligence-programme
- Duration · https://www.getsmarter.com/products/oxford-artificial-intelligence-programme
- Official program page · https://www.getsmarter.com/products/oxford-artificial-intelligence-programme
- Cost terms · https://www.getsmarter.com/terms-and-conditions-for-students
Artificial Intelligence: Implications for Business Strategy
Examine AI through an organizational and managerial lens, with modules on machine learning, generative AI, robotics and business and society. Managers and executives work toward an AI roadmap without a required technological background. The programme is offered in collaboration with MIT Sloan and MIT CSAIL. Its course-completion credential is separate from the broader MIT Sloan Executive Certificate pathway.
- Price
- USD 3850Price details observed 2026-09-28. Displayed programme fee on 28 September 2026, as shown in the United States; not a verified checkout total. Terms source retains its separate 18 September observation date. A time-limited promotion was displayed on 28 September 2026. The final price requires checkout confirmation.Official source · Checked ; Official source · Checked
- Duration
- 6 weeks excluding orientation6–8 hours per week.Official source · Checked
- Format
- Online cohort-based short courseself-paced study within the cohort.Official source · Checked
- Credential
- Certificate of completionOfficial source · Checked
- Prerequisites
- The programme addresses managers and executives without requiring a data-scientist, software-engineer or technological background.Official source · Checked
Sources ↗
- Price · https://www.getsmarter.com/products/mit-sloan-artificial-intelligence-implications-for-business-strategy-online-program
- Duration · https://www.getsmarter.com/products/mit-sloan-artificial-intelligence-implications-for-business-strategy-online-program
- Official program page · https://www.getsmarter.com/products/mit-sloan-artificial-intelligence-implications-for-business-strategy-online-program
- Cost terms · https://www.getsmarter.com/terms-and-conditions-for-students
Implementing Agentic AI: Building Your Organizational Playbook
Explore how AI agents operate, how an organizational process can become an agent-driven workflow, and how governance and risk management affect deployment. The course involves developing an implementation playbook and addresses both technical and nontechnical leaders. The playbook is a learning activity, not a guarantee of a production-ready system. Credential, assessment and support arrangements require provider confirmation; the dated details are set out below.
- Price
- USD 1900Displayed programme fee on 24 September 2026, as shown in the United States; not a verified checkout total. Terms source retains its separate 18 September observation date.Official source · Checked ; Official source · Checked
- Duration
- 3 weeks excluding orientation4–5 hours per week.Official source · Checked
- Format
- Online cohort-based short courseself-paced study within the cohort.Official source · Checked
- Credential
- Credential arrangements require provider confirmationOfficial source · Checked ; Official source · Checked
- Prerequisites
- The page addresses technical and nontechnical leaders and business professionals. A formal prerequisite was not established in the programme page reviewed on 18 September 2026; this is not a claim that no coding is required.Official source · Checked
Sources ↗
- Price · https://www.getsmarter.com/products/mit-sloan-implementing-agentic-ai-program
- Duration · https://www.getsmarter.com/products/mit-sloan-implementing-agentic-ai-program
- Official program page · https://www.getsmarter.com/products/mit-sloan-implementing-agentic-ai-program
- Credential details · https://www.getsmarter.com/terms-and-conditions-for-students
Retired (2)
Study guide for Exam AI-900: Microsoft Azure AI Fundamentals
Microsoft Azure AI Fundamentals exam AI-900 assessed foundational knowledge of AI workloads, machine learning, computer vision, natural language processing, generative AI, and responsible AI considerations on Azure. Microsoft retired the exam on June 30, 2026, so this study guide is now useful as a reference to the former scope rather than as preparation for a currently schedulable exam. The source says it was intended for technical and non-technical candidates; data science and software-engineering experience were not required, although basic cloud and client-server awareness could help. It is not for someone seeking a current Microsoft exam or credential path.
- Credential
- certification
Sources ↗
- Retirement : https://techcommunity.microsoft.com/blog/skills-hub-blog/the-ai-job-boom-is-here-are-you-ready-to-showcase-your-skills/4494128
- Official program page : https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-900
- Credential details : https://learn.microsoft.com/en-us/credentials/support/credential-expiration-policy
Study guide for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution
Exam AI-102 covered designing and implementing Microsoft Azure AI solutions, including generative AI, agents, computer vision, natural language processing, and knowledge mining. Microsoft retired the exam on June 30, 2026, so it is not for new candidates seeking a currently schedulable certification exam. Its former audience was Azure AI engineers who build, integrate, deploy, monitor, and maintain end-to-end AI solutions. The source expects development experience with Python or C#, REST APIs and SDKs, familiarity with the Azure AI portfolio and data-storage options, and the ability to apply responsible AI principles. The study guide remains useful for understanding the retired exam scope, but not as proof that the credential can still be earned.
- Duration
- 100 minutes for the former exam assessmentnot preparation time
- Level
- Intermediate
- Credential
- certification
- Prerequisites
- Experience developing with Python or C#, using REST APIs and SDKs, understanding Azure AI portfolio components and data storage options, and applying responsible AI principles
Sources ↗
- Duration : https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/
- Retirement : https://techcommunity.microsoft.com/blog/skills-hub-blog/the-ai-job-boom-is-here-are-you-ready-to-showcase-your-skills/4494128
- Official program page : https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/
- Credential details : https://learn.microsoft.com/en-us/credentials/support/credential-expiration-policy
- Credential details : https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-102
- ChatGPT for Data Science
- Machine Learning in Python
- Machine Learning with Decision Trees and Random Forests
- Natural Language Processing Specialization
- DeepLearning.AI TensorFlow Developer Professional Certificate
- Mathematics for Machine Learning Specialization
- Convolutional Neural Networks with TensorFlow in Python
- Deep Learning with Pytorch
- Speech Recognition with Python
- TensorFlow: Data and Deployment Specialization
- AI for Medicine Specialization
- TensorFlow: Advanced Techniques Specialization
- Machine Learning with K-Nearest Neighbors
- Machine Learning with Naïve Bayes
- Machine Learning with Support Vector Machines
- Generative AI with Large Language Models
- AI in Healthcare Specialization
- Mathematics for Machine Learning and Data Science Specialization
Data Analysis with ChatGPT
365 Data Science's 'Data Analysis with ChatGPT' is a basic-level online course designed to enhance productivity through AI-driven data tasks. Instructed by Ned Krastev, the 2-hour curriculum teaches learners to leverage ChatGPT for exploratory data analysis, preprocessing, cleaning text, and formatting dates. The course utilizes Excel files for data input and evaluation. Earning the provider-issued course certificate requires passing the course exam with a score of 60% or higher. The provider lists 2.5 CPE credits; however, acceptance depends on individual state boards. Required prerequisites include ChatGPT access, basic data familiarity, and Microsoft Excel, while introductory Excel and generative AI knowledge are recommended. Pricing observations in the United States on 15 October 2026 indicate platform subscription access rather than a per-course fee.
- Duration
- 2 hours (provider headline; module and exam timings listed separately)
- Level
- Basic
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Access to ChatGPT, Basic familiarity with data concepts, Microsoft Excel (any recent version, such as Excel 2019, 2021, or Microsoft 365). Recommended advanced preparation: Introduction to Excel, Intro to ChatGPT and Generative AI.
Sources ↗
- Duration : https://365datascience.com/courses/data-analysis-with-chatgpt/
- Official program page : https://365datascience.com/courses/data-analysis-with-chatgpt/
- Credential details : https://365datascience.com/certificates/
- Credential details : https://365datascience.com/support/is-my-certificate-of-program-completion-still-valid/
- Program scope : https://365datascience.com/terms-of-use/
- Program scope : https://365datascience.com/pricing/
Time Series Analysis with Python
365 Data Science's 'Time Series Analysis with Python' is an intermediate-level, online, self-paced course that teaches proven forecasting techniques and manual model selection principles. Instructed by Viktor Mehandzhiyski, the seven-hour curriculum introduces learners to data normalization and visualizing time series types like white noise and random walk. Topics cover AR, MA, ARMA, ARIMA, ARCH, and GARCH models using Python, culminating in practical business case applications and automated model selection with Auto ARIMA. Earning the provider-issued course certificate requires passing the course exam, with general terms specifying a 60% or higher passing grade. The provider lists 11 CPE credits; acceptance depends on the relevant board. Python 3.8 or later, pandas, a code editor, and basic Python programming skills are required, while NumPy familiarity is recommended.
- Duration
- 7 hours (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Format
- 100% online, self-paced course
- Credential
- Provider-issued course certificate
- Prerequisites
- Python (version 3.8 or later), pandas library, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code). Basic familiarity with Python programming is required. Familiarity with NumPy is helpful but not mandatory. Advanced preparation: Statistics, Introduction to Python.
Sources ↗
Introduction to Python
365 Data Science's 'Introduction to Python' is a basic-level, online course that introduces beginners to fundamental programming concepts and Python's technical advantages for data science and machine learning. Instructed by Martin Ganchev, the two-hour curriculum covers variables, data types, basic syntax, conditional statements, functions, sequences, and iterations, concluding with a prime numbers project. Earning the provider-issued course certificate requires passing the course exam, with general terms specifying a 60% or higher passing grade. The provider lists five CPE credits in the Information Technology field of study; acceptance depends on the relevant board. A Jupyter Notebook or JupyterLab setup is explicitly required, but no advanced preparation is necessary.
- Duration
- 2 hours (provider headline; module, practice exam, and project timings listed separately)
- Level
- Basic
- Format
- 100% online, self-paced course
- Credential
- Provider-issued course certificate
- Prerequisites
- Jupyter Notebook or JupyterLab (available through anaconda.com or online platforms like Google Colab). Advanced preparation: None.
Sources ↗
- Duration : https://365datascience.com/courses/introduction-to-python/
- Official program page : https://365datascience.com/courses/introduction-to-python/
- Credential details : https://365datascience.com/certificates/
- Credential details : https://365datascience.com/support/is-my-certificate-of-program-completion-still-valid/
- Program scope : https://365datascience.com/terms-of-use/
- Program scope : https://365datascience.com/pricing/
AWS Certified Data Engineer - Associate
The AWS Certified Data Engineer - Associate is an Associate-level certification targeting professionals with 2-3 years of data engineering experience and 1-2 years of hands-on AWS experience. The 130-minute exam contains 65 questions and costs USD 150 for a single attempt. No prior certification is required. Domains cover core AWS data services, ingesting and transforming data, orchestrating data pipelines, designing models, managing data life cycles, and ensuring data quality. The credential is valid for 3 years. Renew for 3 more years by passing the latest version of this exam or the AWS Certified Generative AI Developer - Professional exam (certification must be active).
- Price
- USD 150USD 150 for one attempt; foreign-exchange rates, regional pricing, optional preparation and repeat attempts are separate.
- Duration
- 130 minutes for the exam assessmentnot preparation time
- Level
- Associate
- Format
- Certification examQuestions: 65 questions.
- Credential
- Professional certification
- Prerequisites
- No required prerequisites. Target profile: equivalent of 2-3 years of experience in data engineering or data architecture and a minimum of 1-2 years of hands-on experience with AWS services.
Sources ↗
- Price : https://aws.amazon.com/certification/certified-data-engineer-associate/
- Duration : https://aws.amazon.com/certification/certified-data-engineer-associate/
- Official program page : https://aws.amazon.com/certification/certified-data-engineer-associate/
- Credential details : https://aws.amazon.com/certification/recertification/
Machine Learning in Production
The Machine Learning in Production course by DeepLearning.AI on Coursera is an intermediate-level program designed for early-career practitioners and software engineers. Instructed by Andrew Ng, the curriculum teaches how to conceptualize integrated systems that continuously operate in production and solve challenges unique to production environments. Students learn to build data pipelines, establish model baselines, address concept drift, and deploy machine learning applications. The self-paced online program has a provider estimate of 3 weeks at 5 hours a week to complete, while the headline states 1 week at 10 hours a week. Earning the shareable provider-issued course certificate requires paying for the course and completing 6 assignments. As captured on 2 October 2026, the course is taught in English.
- Duration
- 1 week at 10 hours a week
- Level
- Intermediate level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Working knowledge of AI and deep learning, intermediate Python skills, and experience with a deep learning framework (TensorFlow, Keras, or PyTorch). Recommended: Completion of the updated Deep Learning Specialization.
Sources ↗
Google Advanced Data Analytics Professional Certificate
The Google Advanced Data Analytics Professional Certificate is a 7-course online, self-paced program for individuals with foundational data analytics experience. The curriculum provides over 200 hours of instruction in Python, Tableau, statistical analysis, and machine learning models, culminating in a capstone project. Recommended completion is 6 months at 10 hours a week. The program assumes prior knowledge of data analysis and requires understanding of SQL and programming concepts. Completing the program earns a Google certificate and an ACE recommendation for up to 9 college credits. As shown in the US on 2 October 2026, the subscription is 49 USD per month; the provider estimates most learners can complete it for under 300 USD total, which is not a fixed completion cost.
- Price
- Google Advanced Data Analytics Professional Certificate : USD 49 / month regularNo promotional price stated.
Region, access and offer terms
US scope; prices may vary in other countries.
No promotional price stated in the checked source.
As of 2 October 2026 in the US, the Google Advanced Data Analytics programme costs 49 USD per month following a seven day free trial. The provider estimates most learners finish the certificate for under 300 USD total. This is an estimated cost based on typical completion time, not a fixed price. In the U.S. and Canada, Coursera charges $49 per month after the initial 7-day free trial period. The Google Advanced Data Analytics Certificate can be completed in less than 6 months at under 10 hours per week of part-time study, so most learners can complete the certificate for less than $300 USD.
- Duration
- Less than 6 months (headline estimate)6 months at 10 hours a week (completion estimate); over 200 hours of instruction (lesson hours).
- Level
- Advanced level
- Format
- Online, self-paced
- Credential
- Provider-issued course certificate
- Prerequisites
- Assumes prior knowledge of foundational analytical principles, skills, and tools. These include data types, data strategy, data integrity, data cleaning, data aggregation, data analysis, and best practices when information-sharing. It also requires an understanding of spreadsheets, databases and structured query language, programming concepts, data visualization, and dashboards. Designed for people working in the field of data analytics or for those with foundational skills from the Google Data Analytics Certificate or a similar program.
Sources ↗
- Price : https://www.coursera.org/professional-certificates/google-advanced-data-analytics
- Duration : https://www.coursera.org/professional-certificates/google-advanced-data-analytics
- Official program page : https://www.coursera.org/professional-certificates/google-advanced-data-analytics
- Provider subscription terms : https://www.coursera.org/professional-certificates/google-advanced-data-analytics
Intro to MLOps
365 Data Science's 'Intro to MLOps' is a basic-level online course aimed at bridging the gap between developing machine learning models and deploying them in production environments. Instructed by Andrew Jones, the curriculum teaches the fundamentals of machine learning operations using the Databricks ecosystem. The course features 3 hours of headline duration, 4 hours of lesson content, 29 exercises, and 1 final exam. Earning the provider-issued course certificate requires completing the course and passing the course exam with a score of 60% or higher. The provider states the course awards 4 CPE credits, though state board acceptance varies. Required prerequisites include an intermediate understanding of Python and basic Git knowledge. Pricing observations in the United States on 3 October 2026 indicate platform subscription access rather than a per-course fee.
- Duration
- 3 hours (provider headline; 4 hours of lessons listed separately)
- Level
- Basic
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Intermediate Understanding of Python, Cursory Understanding of Machine Learning, Basic Understanding of Git. Recommended: Knowledge of CI/CD helpful.
Sources ↗
IBM Data Science Professional Certificate
The IBM Data Science Professional Certificate on Coursera is a beginner-level program designed to prepare individuals for entry-level data scientist roles in the United States. Instructed by the IBM Skills Network Team, the curriculum teaches students how to import, clean, analyze, and visualize data, as well as build machine learning models and pipelines. Learners gain hands-on experience using Python, SQL, Jupyter notebooks, GitHub, and various data science libraries. The self-paced online program has a provider estimate of less than 6 months to complete, while the headline states 4 months at 10 hours a week. Earning the shareable provider-issued course certificate requires completing the 12-course series and a portfolio of data projects. As captured on 3 October 2026, the program is taught in English.
- Duration
- 4 months at 10 hours a week
- Level
- Beginner level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: None. Recommended: Familiarity with computers and high school math; knowledge of calculus and linear algebra is an asset for the last few courses.
Sources ↗
Google Data Analytics Professional Certificate
The Google Data Analytics Professional Certificate by Google on Coursera is a beginner-level program designed to prepare individuals for entry-level roles in data analytics. The curriculum covers data cleaning, analysis, and visualization using tools such as spreadsheets, SQL, Tableau, and Python. Students learn to process data, create dashboards, and present findings. The self-paced online program features an estimated completion time of less than 6 months at under 10 hours a week, with over 180 hours of instruction and hundreds of practice-based assessments. Earning the shareable provider-issued course certificate requires completing the 9 course series and a capstone project. As captured on 3 October 2026, the course is taught in English.
- Price
- Google Data Analytics Professional Certificate : USD 49 / month regularNo promotional price stated.
Region, access and offer terms
As shown in the United States on 3 October 2026.
No promotional price stated in the checked source.
The FAQ describes a subscription of $49 per month after a 7-day free trial in the U.S. and Canada, with an estimated total of less than $300 USD for most learners. Financial aid is available. In the U.S. and Canada, Coursera charges $49 per month after the initial 7-day free trial period. The Google Data Analytics Certificate can be completed in less than 6 months at under 10 hours per week of part-time study, so most learners can complete the certificate for less than $300 USD. In other countries where Google Career Certificates are available, your cost may be lower.
- Duration
- 6 months at 10 hours a week
- Level
- Beginner level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: None. No degree or experience required. Recommended: None.
Sources ↗
- Price : https://www.coursera.org/professional-certificates/google-data-analytics
- Duration : https://www.coursera.org/professional-certificates/google-data-analytics
- Official program page : https://www.coursera.org/professional-certificates/google-data-analytics
- Provider subscription terms : https://www.coursera.org/professional-certificates/google-data-analytics
IBM Data Engineering Professional Certificate
The IBM Data Engineering Professional Certificate program on Coursera is a beginner-level series of 16 courses offered by IBM. The curriculum covers foundational data engineering skills including Python programming, SQL, relational databases, NoSQL, Apache Spark, and building data pipelines. Students learn to use tools like MongoDB, Hadoop, and Airflow. Instructed by the IBM Skills Network Team, the self-paced online program has a provider estimate of less than 5 months to complete, while the headline states 6 months at 10 hours a week. Earning the shareable provider-issued course certificate requires completing the hands-on labs and projects throughout the program. As captured on 3 October 2026, the program is taught in English.
- Duration
- 6 months at 10 hours a week
- Level
- Beginner level
- Format
- Completely online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Basic IT literacy, knowledge of IT infrastructure, and familiarity working with Windows, Linux, or MacOS. Recommended: Prior computer programming experience and high school math.
Sources ↗
Fully Automated MLOps
365 Data Science's 'Fully Automated MLOps' is an intermediate-level online course designed to teach learners how to build and manage robust machine learning pipelines. Instructed by Stefan Micic, the 1-hour provider headline duration covers MLOps principles, automated data ingestion, deployment strategies, and continuous model monitoring. Earning the provider-issued course certificate requires both completing the course and passing the associated course exam with a score of 60% or higher. The provider lists 2.5 CPE credits; however, acceptance depends on individual state boards. Required prerequisites include Python 3.8 or later, MLflow, Docker, AWS access, and basic MLOps understanding, while introductory Python machine learning and AWS knowledge are recommended advanced preparation. Pricing observations in the United States on 3 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 1 hour (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Python (version 3.8 or later), MLflow, Docker, and a code editor or IDE (e.g., VS Code or Jupyter Notebook), Access to aws.amazon.com and a free AWS account, Basic understanding of MlOps. Recommended advanced preparation: Machine Learning in Python, Introduction to AWS Cloud.
Sources ↗
Gradient Boosting Made Easy: XGBoost, LightGBM & Friends
365 Data Science's 'Gradient Boosting Made Easy: XGBoost, LightGBM & Friends' is an intermediate-level online course that explores advanced machine learning techniques for tabular data. Instructed by Samson Afolabi, the 2-hour provider headline duration covers the implementation of Gradient Boosted Trees using popular libraries like XGBoost, LightGBM, and CatBoost. Learners are guided through decision trees, hyperparameter tuning, and deploying models into production. Earning the provider-issued course certificate requires both completing the course and passing the associated course exam with a score of 60% or higher. The provider states the course awards 4 CPE credits. Required prerequisites include Python programming, scikit-learn, basic machine learning concepts, and command-line usage. Pricing observations in the United States on 3 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 2 hours (provider headline; module and exam timings listed separately)
- Level
- Intermediate
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Good knowledge of Python programming, Familiarity with the scikit-learn library, Understanding of basic machine learning concepts e.g. Linear Regression, Eagerness to learn and apply new tools, Basic knowledge of Bash/command line usage. Recommended advanced preparation: None.
Sources ↗
AI agent engineer
365 Data Science's AI agent engineer career track is a 100% online sequence of ten courses with 36 hours of listed content, labelled intermediate. It moves from AI fundamentals to agent architecture, model context protocols (MCPs), LangChain and LangGraph workflows with memory, multi-agent and human-in-the-loop patterns, agent evaluation and AI ethics. The page also lists four projects, including a LangChain Q&A chatbot. The provider says no prior AI experience is needed to start. Its certification requires finishing the track and passing a final exam. As shown in the United States on 3 October 2026, access sits in the Self-study plan at USD 29 a month billed annually; there is no fixed completion price.
- Duration
- 36 hours of content (provider-listed)
- Level
- Intermediate
- Format
- 100% online career track
- Credential
- Provider-issued certification
- Prerequisites
- No formal prerequisite is stated. The provider says prior AI experience is not needed to start.
Sources ↗
Machine learning scientist
365 Data Science's machine learning scientist career track is a 100% online sequence of ten courses with 29 hours of listed content, labelled advanced. The listed curriculum covers linear algebra and feature selection, math for ML, machine learning in Python, and algorithm courses on Naïve Bayes, k-nearest neighbors, decision trees and random forests, support vector machines, and ridge and lasso regression, plus two A-Z overviews. Finishing the track earns a 365 certification; 365's general terms require passing course and career-track exams at 60% or above. As shown in the United States on 3 October 2026, access sits in the Self-study plan at USD 29 a month billed annually; there is no fixed completion price.
- Duration
- 29 hours of content (provider-listed)
- Level
- Advanced
- Format
- 100% online career track
- Credential
- Provider-issued certification
- Prerequisites
- No formal prerequisite is stated on the track page. The provider labels the track advanced.
Sources ↗
Data scientist
365 Data Science's data scientist career track is a 100% online sequence of ten courses with 69 hours of listed content, labelled intermediate. It builds statistics, probability, mathematics, Python and SQL foundations, then teaches machine learning in Python and deep learning with TensorFlow 2, adds product management for AI and data science, and ends with portfolio, resume and interview preparation. The AI content is two of the ten courses plus the AI product course: a data science path with an AI component. Finishing earns a 365 certification after exams at 60% or above. As shown in the United States on 3 October 2026, access sits in the Self-study plan at USD 29 a month billed annually.
- Duration
- 69 hours of content (provider-listed)
- Level
- Intermediate
- Format
- 100% online career track
- Credential
- Provider-issued certification
- Prerequisites
- No formal prerequisite is stated on the track page. The provider labels the track intermediate.
Sources ↗
Claude Certified Architect - Foundations
Claude Certified Architect - Foundations (CCAR-F) is Anthropic's certification exam on tradeoff decisions when building production solutions with Claude Code, the Claude Agent SDK, the Claude API and the Model Context Protocol. It is open only to people at Claude Partner Network organizations. The exam has 60 multiple-choice and multiple-response items in 120 minutes, built on 4 scenarios drawn from a bank of 6, across five domains led by Agentic Architecture and Orchestration (27%). A scaled score of 720 passes. Pearson VUE delivers it in English, online or at a test center; the credential is valid for 12 months. No hiring evidence exists yet. As shown in the United States on 7 October 2026, the exam fee is USD 125.
- Price
- USD 125As shown in the United States on 7 October 2026, the official exam page displays Purchase | $125, and the certifications page and exam guide list the exam fee as $125 USD. Each retake costs the full fee again. Taxes are not stated on the exam pages.
- Duration
- 120 minutes to answer the exam questionsabout 135 minutes of total seat time including check-in, instructions and a brief survey. Not preparation time.
- Level
- Foundations
- Format
- Proctored certification exam (online or at a Pearson VUE test center), registered and paid on Anthropic Partner Academyavailable only to people at Claude Partner Network organizations Questions: 60.
- Credential
- industry certification
- Prerequisites
- Open only to people at Claude Partner Network organizations: registration needs a partner email address on a recognized company domain, and candidates must be at least 18. The exam guide says the typical candidate has 6+ months of practical experience building with Claude APIs, Agent SDK, Claude Code and MCP; the captured guide names no mandatory prerequisite course.
Sources ↗
- Price : https://anthropic-partners.skilljar.com/claude-certified-architect-foundations-certification
- Duration : https://anthropic-partners.skilljar.com/page/faq-certifications
- Official program page : https://anthropic-partners.skilljar.com/claude-certified-architect-foundations-certification
- Modules or exam domains : https://everpath-course-content.s3-accelerate.amazonaws.com/instructor%2F6nizmqk8tpzpfjvt6qmmav7rh%2Fpublic%2F1783542750%2FClaude+Certified+Architect+%E2%80%93+Foundations+Exam+Guide.pdf
- Credential details : https://anthropic-partners.skilljar.com/page/policies-certifications
- Program scope : https://everpath-course-content.s3-accelerate.amazonaws.com/instructor%2F34hhd92iyp94a0gtbr15cy5jk%2Fpublic%2F1782870704%2FAnthropic+Certification+Exam+Policy.pdf
- Cost terms : https://anthropic-partners.skilljar.com/page/partner-certifications
AWS Certified Machine Learning - Specialty
AWS retired the Machine Learning - Specialty certification: the last day to take its exam was March 31, 2026, so it can no longer be earned. Holders keep an active certification for 3 years from the date they earned it and can keep sharing the Credly badge in that period; recertifying by retake was possible only until March 31, 2026. The exam covered building, training, tuning and deploying ML models on AWS, in 180 minutes with 65 questions. In its retirement FAQ, AWS points ML candidates to AWS Certified Machine Learning Engineer - Associate. As shown in the United States on 3 October 2026, MLA-C01 remains in Japanese, Korean and Simplified Chinese, with an English MLA-C02 beta open.
- Duration
- 180 minutes for the former examnot preparation time
- Level
- Specialty
- Format
- Proctored certification exam (retired; Pearson VUE test center or online proctored when offered)Questions: 65.
- Credential
- industry certification
- Prerequisites
- No prior certification is required. Per AWS, the ideal candidate has 2 or more years developing, architecting and running ML or deep learning workloads in the AWS Cloud.
Sources ↗
Microsoft Certified: Azure Data Scientist Associate (Exam DP-100)
Exam DP-100 led to Microsoft Certified: Azure Data Scientist Associate, covering ML workloads on Azure with Azure Machine Learning and MLflow: designing ML solutions, exploring data and running experiments, training and deploying models, and optimizing language models for AI applications. Microsoft retired the exam on June 1, 2026, and the certification and its renewal assessment are retired, so it can no longer be earned or renewed. Associate certifications are valid for one year. The captured Microsoft pages name no replacement; the current AI-300 exam covers related ML and generative AI operations on Azure, but we do not call it the official successor. As shown in the United States on 3 October 2026, no price is shown.
- Duration
- Not stated on the captured pagesthe exam was retired on June 1, 2026
- Level
- Intermediate
- Format
- Proctored certification exam (retired)
- Credential
- certification
- Prerequisites
- Subject matter expertise in applying data science and machine learning to implement and run ML workloads on Azure, plus knowledge of optimizing language models for AI applications using Azure AI (audience profile).
Sources ↗
- Duration : https://learn.microsoft.com/en-us/credentials/certifications/azure-data-scientist/
- Retirement : https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-100
- Official program page : https://learn.microsoft.com/en-us/credentials/certifications/azure-data-scientist/
- Credential details : https://learn.microsoft.com/en-us/credentials/support/credential-expiration-policy
Senior data scientist
365 Data Science's senior data scientist career track is a 100% online, advanced sequence with 34 hours of listed content, designed as the next step after its Data Science Career Track. The track page lists ten courses: one optional, seven required and two electives. The AI content is machine learning and deep learning: ML algorithms, the ML process from problem definition to deployment, ML business applications, deep learning with PyTorch, and convolutional neural networks with TensorFlow, plus ChatGPT for data science. Completion earns a Senior Data Scientist Certificate. As shown in the United States on 4 October 2026, access sits in the Self-study plan at USD 29 a month billed annually; there is no fixed completion price.
- Duration
- 34 hours of content (provider-listed)
- Level
- Advanced
- Format
- 100% online career track
- Credential
- Provider-issued certificate
- Prerequisites
- No formal prerequisite is stated on the track page. The provider labels it its advanced career track, designed as the next step after completing its Data Science Career Track.
Sources ↗
Agentic AI
Agentic AI is an intermediate DeepLearning.AI course taught by Andrew Ng, self-paced, with 31 video lessons, 7 code examples and 8 graded assignments in five modules. It teaches four agentic design patterns, reflection, tool use, planning and multi-agent workflows, built in Python from first principles, plus evaluations, error analysis and cost and latency tuning. The page shows an update date of Feb 2, 2026; it does not state a launch date. The certificate needs a Pro membership and completed assessments; free auditing gives videos and the forum, with no certificate. As shown in the United States on 4 October 2026, Pro costs USD 25 a month billed annually or USD 30 billed monthly; there is no fixed course price.
- Duration
- 9 hours 55 minutes of content (provider-listed as 9h55m on the course page)content time, not a completion-time promise
- Level
- Intermediate
- Format
- Online, self-paced course with 31 video lessons, 7 code examples and 8 graded assignments
- Credential
- Course completion certificate
- Prerequisites
- No formal admission prerequisite is stated on the captured page. The provider writes the course for professionals with intermediate-level Python programming skills and a basic understanding of large language models and APIs.
Sources ↗
Microsoft Certified: Agentic AI Business Solutions Architect Expert (Exam AB-100)
Exam AB-100 leads to Microsoft Certified: Agentic AI Business Solutions Architect Expert, for solution architects who design AI and agent solutions across Dynamics 365, Power Platform, Copilot Studio and Microsoft Foundry. It measures three skill areas: plan (25-30%), design (25-30%) and deploy (40-45%) AI-powered business solutions. Passing the exam is not enough: Microsoft also requires one prerequisite Associate-level certification from its listed set. The passing score is 700, and the English exam will be updated on October 14, 2026. Expert certifications expire annually and renew through a free online assessment. As shown in the United States on 4 October 2026, no exam price is displayed; Microsoft says the price depends on where the exam is proctored.
- Duration
- Exam length is not stated on the captured pagesnot preparation time.
- Level
- Expert
- Format
- Proctored certification exam
- Credential
- certification
- Prerequisites
- Passing AB-100 is not enough on its own: you must also hold at least one prerequisite Associate-level certification. The exam page lists 15 qualifying certifications (MB-280, PL-200, MB-330, PL-400, MB-230, MB-310, MB-500, MB-800, MB-820, AI-300, AI-103, AB-620, AB-210, AB-410, AB-250); the certification page lists 13 of them, without MB-280 and PL-200.
Sources ↗
- Duration : https://learn.microsoft.com/en-us/credentials/certifications/exams/ab-100/
- Official program page : https://learn.microsoft.com/en-us/credentials/certifications/agentic-ai-business-solutions-architect/
- Modules or exam domains : https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ab-100
- Credential details : https://learn.microsoft.com/en-us/credentials/certifications/renew-your-microsoft-certification-faq
Agentic AI Program
Stanford Online's Agentic AI program, from the Stanford School of Engineering, adapts a graduate-level Stanford curriculum taught by Adjunct Professor Chowdhery and Assistant Professor Mirhoseini for working professionals. It is 100% online and on demand, with 90 days of access and about 30 hours of video and coding assignments, covering test-time scaling, verification, self-improvement, tool use, memory, planning and agent evaluation. A short application comes first; Python, LLM APIs and basic machine learning are expected. Completion earns a Stanford Certificate of Completion as a digital badge. As shown in the United States on 4 October 2026, tuition is USD 1,650; OpenRouter tokens for assignments, estimated at about USD 100, are extra. The page states no launch date.
- Price
- USD 1650As shown in the United States on 4 October 2026, the official program page displays Tuition $1,650 for an individual enrollment with 90 days of access. Assignments also need 100M tokens bought separately from OpenRouter.ai; the provider estimates about $100 of additional compute expenses. Taxes are not stated.
- Duration
- 90 days access, 30 hours to earn the certificate (provider-listed)
- Level
- Graduate-level curriculum adapted for working professionals (provider wording)
- Format
- 100% online, on-demand course with assignments and two optional live sessionsStanford School of Engineering professional certificate program
- Credential
- Certificate of Completion
- Prerequisites
- A short application (about 15 minutes) before enrolling. Python programming experience, basic familiarity with LLMs and LLM APIs, and a basic understanding of machine learning concepts such as those in CS229 / XCS229.
Sources ↗
No Code and Agentic AI
No Code and Agentic AI is a 14-week online MIT Professional Education program, offered with Great Learning, that teaches AI and machine learning without writing code. Weekly units move from LLMs and prompt engineering through clustering, regression, classification and recommendation systems to RAG workflows, evaluating generative AI, single agents and multi-agent systems, with three project weeks and a learning break; four self-paced modules add deep learning, computer vision, responsible AI and time series. Mentors run small-group sessions. Completion earns a certificate of completion and 10 CEUs are listed. As shown in the United States on 4 October 2026, the course fee is USD 2,850 for the session dated Oct 10, 2026 to Feb 14, 2027.
- Price
- USD 2850As shown in the United States on 4 October 2026, the official course page displays a Course Fee of $2,850 for the online session dated Oct 10, 2026 to Feb 14, 2027. Great Learning manages enrollments, including all payment services and invoicing. Taxes are not stated.
- Duration
- 14 weeks (Oct 10, 2026 - Feb 14, 2027 session listed)
- Format
- Online, 14-week mentored program with recorded lectures, case studies, projects, quizzes, mentor-led sessions and webinarsoffered with Great Learning
- Credential
- Certificate of completion
- Prerequisites
- No formal prerequisite is stated. The page says no-code platforms let professionals use these techniques without prior programming knowledge.
Sources ↗
AWS Certified Machine Learning Engineer - Associate (MLA-C02, beta)
MLA-C02 is the beta of the updated AWS Certified Machine Learning Engineer - Associate exam. It covers building, deploying, operating and securing ML and AI solutions on AWS, now including foundation models, Amazon Bedrock, RAG and agentic workflows, across four domains weighted 28%, 24%, 24% and 24%. Beta registration opened September 1, 2026 and beta delivery began September 29, 2026; general availability dates are TBD. The beta is English only, with 85 questions in 170 minutes and results typically within 5 business days. The certification is valid 3 years. As shown in the United States on 4 October 2026, the beta exam costs USD 75 (beta pricing). This record is separate from MLA-C01.
- Price
- USD 75As shown in the United States on 4 October 2026, the AWS certification page lists the MLA-C02 beta exam at $75 USD, labelled beta pricing. The price for general availability is not stated; general availability registration and delivery dates are TBD. Tax treatment is not stated on the captured beta page; optional preparation is separate from the exam fee.
- Duration
- Beta exam: 170 minutes for 85 questionsnot preparation time
- Level
- Associate
- Format
- Proctored certification exam, beta version (Pearson VUE testing center or online proctored)Questions: 85.
- Credential
- industry certification
- Prerequisites
- No prerequisite certification is stated on the captured pages. The exam guide recommends at least 1 year of experience using Amazon SageMaker AI, Amazon Bedrock and other AWS services for ML engineering, plus at least 1 year in a related role, with experience in both traditional ML and generative AI.
Sources ↗
- Price : https://aws.amazon.com/certification/certified-machine-learning-engineer-associate/
- Duration : https://aws.amazon.com/certification/certified-machine-learning-engineer-associate/
- Official program page : https://docs.aws.amazon.com/aws-certification/latest/machine-learning-engineer-associate-02/machine-learning-engineer-associate-02.html
Artificial Intelligence Professional Program
Stanford Online's Artificial Intelligence Professional Program, from the Stanford School of Engineering, adapts on-campus graduate courses for working professionals. Each 10-week online course runs 10-15 hours per week with recorded lectures, coding and written assignments and a course facilitator. Eight courses are listed, including XCS229 Machine Learning, XCS224N NLP with Deep Learning, XCS234 Reinforcement Learning and XCS231N computer vision. A short application checks Python, calculus, linear algebra and probability. Three program courses, or two plus one AI Graduate Program course, earn the Stanford Professional Certificate in Artificial Intelligence, delivered as a blockchain-verified digital certificate. As shown in the United States on 5 October 2026, tuition is USD 2,045 per course.
- Price
- USD 2045As shown in the United States on 5 October 2026, the official program page displays tuition of $2,045 USD per course for individual enrollments. The Stanford Professional Certificate in Artificial Intelligence needs three program courses, or two program courses plus one AI Graduate Program course, which is priced separately. Group pricing for five or more is by request. Taxes are not stated.
- Duration
- 10 weeks per course, 10-15 hours per week (provider-listed)the certificate needs three courses
- Level
- Graduate-level depth adapted for working professionals (provider wording)
- Format
- 100% online courses from the Stanford School of Engineering, on-demand or on-demand with live elements depending on the courseinstructor-paced cohorts with a course facilitator
- Credential
- Professional certificate
- Prerequisites
- A short application (15-20 minutes) before the first course, to verify the prerequisites: proficiency in Python (some assignments use basic Linux command line workflows), college calculus and linear algebra, and probability theory.
Sources ↗
Artificial Intelligence Graduate Certificate (Online)
Harvard Extension School's Artificial Intelligence Graduate Certificate is a fully online program of four courses taken for graduate credit: one each in foundations of AI, advanced NLP and machine learning, deep learning and computer vision, and AI ethics, governance and law. Courses run in fall, spring and summer terms with live and on-demand options. There is no application; you register for each course. Statistics and basic Python are recommended. You need at least a B in each course and must finish within three years; the page says 8 months is possible at two courses per semester. As shown in the United States on 5 October 2026, the page displays tuition of USD 14,320.
- Price
- USD 14320As shown in the United States on 5 October 2026, the official certificate page displays Tuition $14,320 in its header beside 4 online courses. The cost-of-attendance page it links to was not captured, so per-course tuition and other fees are not established. Taxes are not stated.
- Duration
- Finish in 8 months to 3 years (provider-listed)most students complete within 18 to 24 months
- Level
- Graduate
- Format
- 4 online courses taken for graduate creditsynchronous (live) and asynchronous (on-demand) course options; flexible pace
- Credential
- Graduate certificate
- Prerequisites
- No formal application: you register for each course. Recommended: statistics and basic programming at the level of STAT 100 or the equivalent; learners with no Python are advised to take CSCI 7, CSCI 50 or the equivalent first.
Sources ↗
- Price : https://extension.harvard.edu/academics/programs/artificial-intelligence-graduate-certificate/
- Duration : https://extension.harvard.edu/academics/programs/artificial-intelligence-graduate-certificate/
- Official program page : https://extension.harvard.edu/academics/programs/artificial-intelligence-graduate-certificate/
Designing and Building AI Products and Services
Designing and Building AI Products and Services is a 10-week online MIT xPRO program, delivered with Emeritus, that teaches technical product leaders, technologists, consultants and founders to design, build and pitch AI-based products. Nine modules cover the AI design process, machine learning and deep learning fundamentals, generative AI with RAG and chain-of-thought prompting, human-computer interaction and superminds; three live sessions cover agentic AI and the Model Context Protocol. Expect about 6 hours per week; the content assumes calculus, linear algebra, statistics and probability. Passing at 70 percent earns a certificate of completion and 6 CEUs. The fee did not render on the page captured from the United States on 5 October 2026: no accepted price.
- Duration
- 10 weeks, online + live online, 6 hours per week (provider-listed)
- Format
- 10-week online program with recorded lectures, live online sessions, knowledge checks, a capstone AI product proposaldelivered with Emeritus
- Credential
- Certificate of completion
- Prerequisites
- No application is described on the captured page. The provider notes that the content assumes previous knowledge of calculus, linear algebra, statistics and probability, and that basic Python experience will be beneficial.
Sources ↗
Retrieval Augmented Generation (RAG)
Retrieval Augmented Generation (RAG) is an intermediate DeepLearning.AI course taught by Zain Hasan, self-paced, with 49 video lessons, 9 code examples and 10 graded assignments across five modules, listed at 26h3m of content. It covers retrievers, keyword, semantic and hybrid search, vector databases with Weaviate, prompt design, evaluation and RAG systems in production, with labs on news, e-commerce and healthcare data. Intermediate Python is required. The certificate needs a paid route, PRO on DeepLearning.AI, whose amounts did not render on the captured page, or Coursera; free audit gives no certificate. As shown in the United States on 5 October 2026, Coursera Plus, which includes the course, costs USD 59 a month or USD 399 a year.
- Duration
- Coursera page (5 October 2026): 3 weeks at 10 hours a week, modules of 6, 6, 6, 7 and 6 hours to complete. DeepLearning.AI course page (5 October 2026), a different estimate: 26h3m of content and about a month at about 5 hours per week. Both are recorded as shownno combined duration is computed.
- Level
- Intermediate
- Format
- Online, self-paced course with 49 video lessons, 9 code examples and 10 graded assignments in five modulesalso offered on Coursera
- Credential
- Course completion certificate
- Prerequisites
- No admission requirement is stated on the captured pages. Recommended background: intermediate Python skills are required; basic knowledge of generative AI and high school level math is helpful.
Sources ↗
Applied AI and Data Science Program
MIT Professional Education's Applied AI and Data Science Program, formerly the Applied Data Science Program, is a live online program with curriculum developed and taught by MIT faculty and delivered with Great Learning. The page lists 15 weeks as the course length and, in its curriculum, 14 weeks: foundations, core weeks on machine learning, deep learning, recommendation systems and generative AI including RAG and agentic AI, a project week and a 3-week capstone. Mentors run small-group sessions. Prerequisites are basic programming and statistics. Completion earns a certificate of completion; 16 CEUs are listed. As shown in the United States on 5 October 2026, the course fee is USD 3,900 for the session dated Nov 21, 2026 to Mar 28, 2027.
- Price
- USD 3900As shown in the United States on 5 October 2026, the official course page displays a Course Fee of $3,900 for the live online session dated Nov 21, 2026 to Mar 28, 2027. Taxes are not stated.
- Duration
- The page lists both: Course Length "15 Weeks" (session Nov 21, 2026 - Mar 28, 2027) and, in its curriculum section, "The program is 14 weeks long"pre-work adds 11 hours of video content
- Format
- Live online program with MIT faculty lectures, mentored small-group sessions, hands-on projects and a capstonedelivered in collaboration with Great Learning
- Credential
- Certificate of completion
- Prerequisites
- Prerequisites: basic knowledge of computer programming and statistics (provider wording). Pre-work covers Python and statistics.
Sources ↗
Machine Learning (XCS229)
XCS229 Machine Learning is a Stanford School of Engineering professional course with prerecorded lectures, scheduled coursework and live sessions, taught by Tengyu Ma and Christopher Ré. It gives a broad introduction to machine learning and statistical pattern recognition: supervised learning, kernels and support vector machines, unsupervised learning, component analysis, deep learning basics and learning theory, with algorithms built from scratch. The listed session runs Nov 16 - Feb 7, 2027 at 10-15 hours per week. A score of 70% or higher on required assignments earns a Certificate of Achievement. An application checks Python, calculus, linear algebra and probability. It is an AI Professional Program course. As shown in the United States on 5 October 2026, tuition is USD 2,045.
- Price
- USD 2045As shown in the United States on 5 October 2026, the official course page displays Tuition $2,045.00 for an individual enrollment in the Nov 16 - Feb 7, 2027 session; group pricing for five or more is by request. Taxes are not stated.
- Duration
- Nov 16 - Feb 7, 2027 session listed10-15 hours per week (provider-listed); 10 CEU-equivalent units
- Format
- 100% online, on-demand, live: prerecorded lectures with coursework on a set schedule and live online sessions with the teaching teaminstructor-paced cohort
- Credential
- Certificate of Achievement
- Prerequisites
- A short application (15 min) is required before your first course in the AI Professional Program, to demonstrate proficiency in Python (some assignments use basic Linux command line workflows), college calculus and linear algebra, and probability theory. Prior NumPy experience is recommended.
Sources ↗
AI Essentials for Business
AI Essentials for Business is an on-demand Harvard Business School Online course, taught by HBS professors Karim R. Lakhani and Marco Iansiti, on how AI is transforming business. Four modules (The Age of AI, The Rise of Generative AI, Strategy: Network Effects and Learning Effects, and Transformation Journey) take 16-24 hours over 4 weeks, with case-based exercises. It is aimed at business professionals, leaders, aspiring leaders and functional specialists; no prerequisites are stated. Completing the course earns a Certificate of Completion, and it counts toward a Certificate of Specialization when three Digital Transformation and AI courses are completed within 18 months. As shown in the United States on 6 October 2026, the price is USD 1,949.
- Price
- USD 1949As shown in the United States on 6 October 2026, the official course page displays Price $1,949 for this on-demand course. Taxes are not stated.
- Duration
- 4 weeks, 16-24 hours in total, 4-6 hours per module (provider-listed)
- Format
- On-demand online course from HBS Onlinestart anytime; four modules with case-based examples, polls, quizzes and peer discussion
- Credential
- Certificate of completion
- Prerequisites
- No prerequisites are stated on the captured course page.
Sources ↗
- Price : https://online.hbs.edu/courses/ai-essentials-for-business
- Duration : https://online.hbs.edu/courses/ai-essentials-for-business
- Official program page : https://online.hbs.edu/courses/ai-essentials-for-business
- Credential details : https://online.hbs.edu/why-hbs-online/about-our-courses-and-programs/what-you-earn
AI Strategy and Leadership Program: Driving Data and Organizational Transformation
The AI Strategy and Leadership Program is a 12-week online MIT xPRO program, delivered with Emeritus, for executives, directors and managers, consultants and founders who lead AI adoption. Twelve modules run in two phases: AI and data foundations (AI strategy, data strategy, deployment, AI risks, data privacy) and leading AI transformation (leadership, nimble organizations, x-teams, AI governance, culture of innovation), plus eight optional live sessions on topics such as agentic AI and AI regulation. Expect about 5 hours per week; no coding is required. Passing at 70 percent earns a certificate of completion and 6.0 CEUs. The program fee did not render on the page captured from the United States on 6 October 2026: no accepted price.
- Duration
- 12 weeks, online + live online, 5 hours per week (provider-listed)
- Format
- 12-week online program with recorded video lectures, optional live online sessions, discussions, assignments, projects, knowledge checks and a capstonedelivered with Emeritus
- Credential
- Certificate of completion
- Prerequisites
- No coding or technical specialization is required (provider FAQ). No application is described on the captured page.
Sources ↗
Microsoft Certified: AI Transformation Leader (Exam AB-731)
Exam AB-731 leads to Microsoft Certified: AI Transformation Leader, a Beginner-level certification for business decision-makers who guide AI transformation with Microsoft 365 Copilot, Azure AI and Microsoft Foundry without writing code. It measures three skill areas: the business value of generative AI solutions (35-40%), the benefits and capabilities of Microsoft's AI apps and services (35-40%), and an implementation and adoption strategy (20-25%), including responsible AI and governance. The proctored exam lasts 45 minutes and needs a score of 700. The captured pages do not say whether this certification expires. As shown in the United States on 6 October 2026, no exam price is displayed; Microsoft says the price depends on where the exam is proctored.
- Duration
- 45 minutes to complete the exam assessmentnot preparation time
- Level
- Beginner
- Format
- Proctored certification exam
- Credential
- certification
- Prerequisites
- No prerequisite certification is stated on the captured pages. Microsoft says candidates need experience leading adoption or change management in a business context and familiarity with Microsoft 365 services, Microsoft Foundry and general AI capabilities; no coding is expected.
Sources ↗
- Duration : https://learn.microsoft.com/en-us/credentials/certifications/ai-transformation-leader/
- Official program page : https://learn.microsoft.com/en-us/credentials/certifications/ai-transformation-leader/
- Modules or exam domains : https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ab-731
- Credential details : https://learn.microsoft.com/en-us/credentials/certifications/renew-your-microsoft-certification-faq
Claude Certified Developer - Foundations
Claude Certified Developer - Foundations (CCDV-F) is Anthropic's certification exam for engineers who build with the Claude API, Claude Code and the Model Context Protocol. It is open only to people at Claude Partner Network organizations. The exam has 53 multiple-choice and multiple-response items in 120 minutes across eight domains, led by Applications and Integration (33.1%), Model Selection and Optimization (16.8%) and Agents and Workflows (14.7%). A scaled score of 720 passes. Pearson VUE delivers it in English, online or at a test center; the credential is valid for 12 months. Its exam guide dates from July 2026. No hiring evidence exists yet. As shown in the United States on 7 October 2026, the exam fee is USD 125.
- Price
- USD 125As shown in the United States on 7 October 2026, the official exam page displays Purchase | $125, and the certifications page and exam guide list the exam fee as $125 USD. Each retake costs the full fee again. Taxes are not stated on the exam pages.
- Duration
- 120 minutes to answer the exam questionsabout 135 minutes of total seat time including check-in, instructions and a brief survey. Not preparation time.
- Level
- Foundations
- Format
- Proctored certification exam (online or at a Pearson VUE test center), registered and paid on Anthropic Partner Academyavailable only to people at Claude Partner Network organizations Questions: 53.
- Credential
- industry certification
- Prerequisites
- Open only to people at Claude Partner Network organizations: registration needs a partner email address on a recognized company domain, and candidates must be at least 18. No mandatory prerequisites or required courses (exam guide). Recommended, not required: one to five years of software engineering experience, at least six months of hands-on experience with Claude or comparable LLM-based systems, proficiency in Python and/or TypeScript, and fluency with REST APIs and CLI tools.
Sources ↗
- Price : https://anthropic-partners.skilljar.com/claude-certified-developer-foundations-certification
- Duration : https://anthropic-partners.skilljar.com/page/faq-certifications
- Official program page : https://anthropic-partners.skilljar.com/claude-certified-developer-foundations-certification
- Modules or exam domains : https://everpath-course-content.s3-accelerate.amazonaws.com/instructor%2F6nizmqk8tpzpfjvt6qmmav7rh%2Fpublic%2F1783542875%2FClaude+Certified+Developer+%E2%80%93+Foundations+Exam+Guide.pdf
- Credential details : https://anthropic-partners.skilljar.com/page/policies-certifications
- Program scope : https://everpath-course-content.s3-accelerate.amazonaws.com/instructor%2F34hhd92iyp94a0gtbr15cy5jk%2Fpublic%2F1782870704%2FAnthropic+Certification+Exam+Policy.pdf
- Cost terms : https://anthropic-partners.skilljar.com/page/partner-certifications
Claude Certified Associate - Foundations
Claude Certified Associate - Foundations (CCAO-F) is Anthropic's certification exam for professionals who use Claude as a productivity tool in roles such as operations, marketing, project management and communications. It is open only to people at Claude Partner Network organizations and does not count toward Claude Partner Network eligibility. The exam has 60 multiple-choice and multiple-response items in 120 minutes across seven domains, from prompting and output evaluation to governance and responsible use; no coding is needed. A scaled score of 720 passes, and the credential is valid for 12 months. Its exam guide dates from July 2026. No hiring evidence exists yet. As shown in the United States on 7 October 2026, the exam fee is USD 99.
- Price
- USD 99As shown in the United States on 7 October 2026, the official exam page displays Purchase | $99, and the certifications page and exam guide list the exam fee as $99 USD. Each retake costs the full fee again. Taxes are not stated on the exam pages.
- Duration
- 120 minutes to answer the exam questionsabout 135 minutes of total seat time including check-in, instructions and a brief survey. Not preparation time.
- Level
- Foundations
- Format
- Proctored certification exam (online or at a Pearson VUE test center), registered and paid on Anthropic Partner Academyavailable only to people at Claude Partner Network organizations Questions: 60.
- Credential
- industry certification
- Prerequisites
- Open only to people at Claude Partner Network organizations: registration needs a partner email address on a recognized company domain, and candidates must be at least 18. No mandatory prerequisites or required courses, and no software development or API experience is needed (exam guide). Recommended, not required: regular hands-on experience using Claude in a professional setting and a practical understanding of AI limitations such as hallucinations, context constraints and data sensitivity.
Sources ↗
- Price : https://anthropic-partners.skilljar.com/claude-certified-associate-foundations-certification
- Duration : https://anthropic-partners.skilljar.com/page/faq-certifications
- Official program page : https://anthropic-partners.skilljar.com/claude-certified-associate-foundations-certification
- Modules or exam domains : https://everpath-course-content.s3-accelerate.amazonaws.com/instructor%2F6nizmqk8tpzpfjvt6qmmav7rh%2Fpublic%2F1783542847%2FClaude+Certified+Associate+%E2%80%93+Foundations+Exam+Guide.pdf
- Credential details : https://anthropic-partners.skilljar.com/page/policies-certifications
- Credential details : https://anthropic-partners.skilljar.com/page/partner-certifications
- Program scope : https://everpath-course-content.s3-accelerate.amazonaws.com/instructor%2F34hhd92iyp94a0gtbr15cy5jk%2Fpublic%2F1782870704%2FAnthropic+Certification+Exam+Policy.pdf
Practical Deep Learning for Coders
Practical Deep Learning for Coders is fast.ai's free online course for people with some coding experience who want to apply deep learning and machine learning to practical problems. Part 1, recorded in 2022 at the University of Queensland and taught by Jeremy Howard, has 9 lessons of around 90 minutes on computer vision, natural language processing, tabular data, collaborative filtering, random forests and deployment, using PyTorch, fastai, Hugging Face Transformers and Gradio. The only stated prerequisite is about a year of coding, preferably in Python, plus high school math. A separate part 2 runs more than 30 hours. No certificate is mentioned on the page. As shown in the United States on 7 October 2026, the course is free.
- Price
- FreeAs shown in the United States on 7 October 2026, the official course page calls it "A free course designed for people with some coding experience" and says the course book is freely available online.
- Duration
- 9 lessons of around 90 minutes each (part 1, provider-listed)part 2 is a separate video course of more than 30 hours
- Format
- Free online video course (part 1, recorded in 2022 at the University of Queensland), with captioned videos, the course book freely available online and its chapters as Jupyter notebooks
- Prerequisites
- The page states that the only prerequisite is knowing how to code (a year of experience is enough), preferably in Python, and having at least followed a high school math course; it says no special hardware or software and no university math are needed.
Sources ↗
Google Prompting Essentials
Google Prompting Essentials is a beginner, self-paced four-course specialization on writing clear and specific prompts for generative AI tools at work. Its courses cover a prompting framework, everyday work tasks, data analysis and presentations, and using AI as a creative or expert partner, with responsible use and checking outputs for bias and errors. No prior experience is required. Course estimates total 6 hours; the program says under 10 hours. As shown in the United States on 7 October 2026, Coursera charges USD 49 per month after an initial 7-day free trial; financial aid is available. Completion earns a certificate from Google, not a professional certification.
- Price
- Google Prompting Essentials monthly subscription : USD 49 / month regularNo promotional price stated.
Region, access and offer terms
As shown in the United States on 7 October 2026; U.S. and Canada.
No promotional price stated in the checked source.
In the U.S. and Canada, Coursera charges $49 per month after the initial 7-day free trial period. Prices may vary in other countries. Financial aid is available. USD 49 per month after an initial seven-day free trial, as shown in the United States on 7 October 2026. One month of access is not a completion guarantee.
- Duration
- Under 10 hours in the program descriptionThe four course estimates total 6 hours, and Coursera also shows 4 hours to complete; no single guaranteed total or weekly workload is inferred.
- Level
- Beginner
- Format
- Online, self-paced four-course specialization with flexible scheduling.
- Credential
- certificate
- Prerequisites
- No experience required.
Sources ↗
- Price : https://www.coursera.org/specializations/prompting-essentials-google
- Duration : https://www.coursera.org/specializations/prompting-essentials-google
- Official program page : https://www.coursera.org/specializations/prompting-essentials-google
- Provider subscription terms : https://www.coursera.org/specializations/prompting-essentials-google
IBM AI Foundations for Business Specialization
The IBM AI Foundations for Business Specialization on Coursera is a beginner-level program designed for business leaders considering AI solutions. The curriculum introduces the core concepts of artificial intelligence and data science, and presents the AI Ladder framework for deploying AI in an enterprise. Learners explore tools like generative AI and gain skills in big data, cloud computing, and machine learning methods. The self-paced program has a headline estimate of 4 weeks to complete at 10 hours a week, while the FAQ estimates approximately 20 hours in total. Earning the shareable provider-issued course certificate requires completing the 3-course series, which includes checks for understanding. As shown in the United States on 7 October 2026, the program is taught in English.
- Duration
- 4 weeks to complete at 10 hours a week
- Level
- Beginner level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The provider states that no prior experience or knowledge of artificial intelligence, machine learning, or data science is required.
Sources ↗
AI Python for Beginners
The AI Python for Beginners course by DeepLearning.AI on Coursera is a beginner-level program teaching Python programming fundamentals and AI integrations. The curriculum covers basic AI Python coding, automating tasks with loops and dictionaries, working with data and documents using files and CSVs, and extending Python with packages and APIs. Students learn to leverage AI assistants for debugging and concept explanation while building practical AI-powered tools like recipe generators and vacation planners. The self-paced online program has a provider estimate of 2 weeks to complete at 10 hours a week. The FAQ states that earning the shareable certificate requires purchasing the certificate experience and completing the course. The program was reviewed in the United States on 7 October 2026.
- Duration
- 2 weeks at 10 hours a week
- Level
- Beginner level
- Format
- Flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The provider indicates a Beginner level with no stated formal prerequisites, noting the course teaches practical AI applications even if you have never programmed before.
Sources ↗
Introduction to Artificial Intelligence (AI)
IBM's Introduction to Artificial Intelligence (AI) is a beginner-level Coursera course taught by Antonio Cangiano. Its four modules cover AI applications; core concepts such as machine learning, deep learning, neural networks and large language models; how AI and generative AI are changing business and careers; and ethics and AI governance. The page lists 1 week at 10 hours a week, a flexible schedule, 13 assignments, hands-on labs and a final project designing a generative AI solution for an organizational challenge. It is taught in English with a shareable certificate. As shown in the United States on 7 October 2026, no price is stated: the page shows Enroll for free and financial aid, and the certificate needs the purchased Certificate experience.
- Duration
- 1 week at 10 hours a week (provider headline)the four modules are listed at 4, 3, 4 and 3 hours to complete
- Level
- Beginner level
- Format
- Online course on Coursera, flexible schedule, learn at your own pacevideos, readings, graded quizzes, hands-on labs and a final project
- Credential
- Provider-issued course certificate
- Prerequisites
- No prerequisite is listed: the page shows a "Recommended experience" label without details and says the course is suitable for everyone, including professionals, enthusiasts, and students interested in learning the fundamentals of AI.
Sources ↗
AI Strategy
365 Data Science's 'AI Strategy' is a basic-level online course helping executives and managers formulate, evaluate, and scale AI strategies. Instructed by Bernard Marr, the 4-hour provider headline duration covers AI evolution, identifying high-impact use cases, building a data foundation, and executing AI strategy. Earning the provider-issued course certificate requires completing the course and passing the associated course exam with a score of 60% or higher. The provider lists 5 CPE credits; acceptance depends on individual state boards. The required prerequisite is Intro to AI, and advanced preparation includes Data Literacy and Intro to AI. Pricing observations in the United States on 9 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 4 hours (provider headline; module and exam timings listed separately)
- Level
- Basic
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required prerequisite: Intro to AI. Advanced preparation: Data Literacy and Intro to AI.
Sources ↗
Generative AI for Beginners
Generative AI for Beginners (Version 3) is a 21-lesson course by Microsoft Cloud Advocates on the fundamentals of building generative AI applications, published as an open GitHub repository. Learn lessons explain concepts such as large language models, responsible AI and prompt engineering; Build lessons add Python and TypeScript code for text generation, chat, search, image generation, function calling, retrieval-augmented generation and AI agents. Each lesson has a short video introduction, a written lesson and extra resources. Basic Python or TypeScript knowledge is helpful, and the code runs on Azure OpenAI Service, Microsoft Foundry Models, the OpenAI API or Foundry Local. No certificate is mentioned. As shown in the United States on 9 October 2026, the README states no price.
- Duration
- 21 lessons plus a Course Setup lesson (00)no hours or weeks are stated on the captured README
- Format
- Self-paced online course published as an open GitHub repository and site: each lesson has a short video introduction, a written lesson in its README, Python and TypeScript code samples and links to extra resources
- Prerequisites
- The README says basic knowledge of Python or TypeScript is helpful and points absolute beginners to separate Python and TypeScript courses; it lists a GitHub account to fork the repository, and access to Azure OpenAI Service, Microsoft Foundry Models, the OpenAI API or Foundry Local to run the code.
Sources ↗
Advanced Machine Learning and AI Applications in Finance
365 Data Science's 'Advanced Machine Learning and AI Applications in Finance' is an advanced-level online course designed to teach learners how to apply machine learning and AI to real-world financial problems. Instructed by Professor Gerhard Kling, the 3-hour provider headline duration covers predictive modeling for financial time series, portfolio optimization, asset pricing, and reinforcement learning. Earning the provider-issued course certificate requires completing the course and passing the associated course exam with a score of 60% or higher. The provider lists 4 CPE credits; however, acceptance depends on individual state boards. Required prerequisites include Python (Pandas, NumPy), basic understanding of time series analysis, and basic understanding of machine learning. Pricing observations in the United States on 11 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 3 hours (provider headline). Lessons (2 hours) and Practice exams (1 hour) are explicitly listed. The course exam is 90 minutes. There is no inferred elapsed time.
- Level
- Advanced
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Python (Pandas, NumPy), Basic understanding of time series analysis, Basic understanding of machine learning.
Sources ↗
- Duration : https://365datascience.com/courses/advanced-machine-learning-and-ai-applications-in-finance/
- Official program page : https://365datascience.com/courses/advanced-machine-learning-and-ai-applications-in-finance/
- Credential details : https://365datascience.com/certificates/
- Cost terms : https://365datascience.com/pricing/
AI Applications for Business Success
365 Data Science's 'AI Applications for Business Success' is an advanced-level online course instructed by Horia Mărgărit, designed to teach professionals how to leverage artificial intelligence for business value. The 2-hour provider headline duration covers defining SMART goals, conducting SWOT analysis, supply chain analytics, and advanced AI techniques to infer causation using hybrid experiments. Earning the provider-issued course certificate requires completing the course and passing the associated course exam with a score of 60% or higher. The provider lists 3.5 CPE credits; however, acceptance depends on individual state boards. Required prerequisites include Python 3.8 or later, pandas, a code editor, and intermediate Python skills. Pricing observations in the United States on 11 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 2 hours (provider headline; module and exam timings listed separately)
- Level
- Advanced
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Python (version 3.8 or later), pandas library, a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code), and intermediate Python skills. Recommended advanced preparation: Familiarity with basic statistics and linear algebra, Introduction to Python, and Machine Learning in Python.
Sources ↗
IBM Machine Learning Professional Certificate
The IBM Machine Learning Professional Certificate on Coursera is an intermediate-level program designed to prepare individuals for careers in machine learning. Instructed by IBM, the curriculum teaches students to use algorithms and statistical models to analyze data. Learners gain hands-on experience with supervised and unsupervised learning, regression, classification, deep learning, and reinforcement learning using Python, Jupyter Notebooks, and libraries like Scikit-learn and TensorFlow. The self-paced online program has a headline estimate of 3 months to complete at 10 hours a week, while the FAQ estimates 42 to 60 total hours of study. Earning the shareable provider-issued course certificate requires completing the 6-course series and a final capstone project. As shown in the United States on 11 October 2026, the program is taught in English.
- Duration
- 3 months to complete at 10 hours a week
- Level
- Intermediate level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The provider recommends familiarity with programming on a Python development environment, a fundamental understanding of calculus, linear algebra, probability, and statistics, as well as a background in math, statistics, and computer programming.
Sources ↗
AI Engineer in Python
AI Engineer in Python is a Dataquest career path that goes from Python fundamentals to deploying production AI systems. Its 33 courses in 11 steps cover Python and developer tooling, large language model APIs, prompt engineering and tool use, AI apps with FastAPI and Docker, Hugging Face open models, data analysis, statistics, machine learning, deep learning with PyTorch, embeddings, vector databases and retrieval-augmented generation (RAG). It is labelled Beginner friendly: 11 months at 5 hours a week, self paced, 21 projects and a path certificate. As shown in the United States on 12 October 2026, no Premium plan amount is rendered on the captured plans page; Dataquest says certificates require a paid subscription and its courses are not accredited.
- Duration
- 11 months at 5 hours a week (provider headline, shown as "11 months (5 hrs/week)")each of the 33 courses is listed with its own hours on the path outline. Provider estimates, not an elapsed completion promise.
- Level
- Beginner friendly
- Format
- Self-paced online career path with interactive lessons and exercises in the browser and guided projects
- Credential
- Provider-issued certificate
- Prerequisites
- No prerequisite is listed for the path: the Dataquest plans page FAQ says "No prerequisites are required" and that its career paths start from the very basics; the path page labels it "Beginner friendly".
Sources ↗
- Duration : https://www.dataquest.io/path/ai-engineer/
- Official program page : https://www.dataquest.io/path/ai-engineer/
- Credential details : https://support.dataquest.io/en/articles/153-certificates-earning-finding-and-sharing
- Credential details : https://www.dataquest.io/plans/
- Credential details : https://support.dataquest.io/en/articles/28-when-does-my-subscription-expire-and-what-happens-after
- Program scope : https://support.dataquest.io/en/articles/30-requesting-a-refund
- Cost terms : https://support.dataquest.io/en/articles/756-lifetime-plan-terms-and-conditions
PyTorch for Deep Learning Professional Certificate
This DeepLearning.AI Professional Certificate, taught by Laurence Moroney, is an intermediate three-course series on Coursera: PyTorch: Fundamentals, PyTorch: Techniques and Ecosystem Tools, and PyTorch: Advanced Architectures and Deployment. It covers tensors, neural networks and pipelines, TorchVision and Hugging Face for vision and language tasks, transfer learning and fine-tuning, architectures such as ResNet and Transformers, and deployment with ONNX, MLflow, pruning and quantization. Coursera lists 2 months at 10 hours a week; DeepLearning.AI lists 87h42m and about 4 months at 10 hours per week. As shown in the United States on 12 October 2026, Coursera shows no programme price; the DeepLearning.AI Pro membership, which gives the certificate, costs USD 25 a month billed annually or USD 30 billed monthly.
- Duration
- Coursera: 2 months at 10 hours a week, with the three courses listed at 24, 33 and 31 hours. DeepLearning.AI: 87h42m, and its FAQ says the certificate is designed to be completed in about 4 months at 10 hours per week. Provider estimatesnone is an elapsed completion promise.
- Level
- Intermediate level
- Format
- Online Professional Certificate on Coursera, 3 course series, flexible schedule, learn at your own paceDeepLearning.AI lists 77 video lessons, 11 code examples and 24 graded assignments (a graded quiz and a programming assignment in each module)
- Credential
- Professional Certificate
- Prerequisites
- Recommended, not required: the DeepLearning.AI page says familiarity with Python and foundational deep learning concepts, such as those covered in the Deep Learning Specialization by DeepLearning.AI, will help you get the most from this professional certificate. The Coursera page shows a "Recommended experience" label without details.
Sources ↗
- Duration : https://www.coursera.org/professional-certificates/pytorch-for-deep-learning
- Official program page : https://www.coursera.org/professional-certificates/pytorch-for-deep-learning
- Credential details : https://www.deeplearning.ai/specializations/pytorch-for-deep-learning-professional-certificate
Microsoft AI & ML Engineering Professional Certificate
Microsoft's AI & ML Engineering Professional Certificate is an intermediate five-course series on Coursera: Foundations of AI and Machine Learning; AI and Machine Learning Algorithms and Techniques; Building Intelligent Troubleshooting Agents; Microsoft Azure for AI and Machine Learning; and Advanced AI and Machine Learning Techniques and Capstone. It covers AI and ML infrastructure, supervised, unsupervised, reinforcement and deep learning, AI agents, Azure ML workflows, responsible AI and a capstone project. Intermediate Python is required, and an Azure license or free trial is needed. Coursera lists 6 months at 7 hours a week. As shown in the United States on 12 October 2026, no programme price is shown; the page marks it as included with Coursera Plus.
- Duration
- 6 months at 7 hours a week (provider headline)the five courses are listed at 36, 45, 43, 21 and 31 hours, and the FAQ says each course will take approximately 35-40 hours. Provider estimates, not an elapsed completion promise.
- Level
- Intermediate level
- Format
- Online Professional Certificate on Coursera, 5 course series, flexible schedule, learn at your own paceMicrosoft recommends taking the courses in the order listed; ends with a capstone project
- Credential
- Professional Certificate
- Prerequisites
- Intermediate programming knowledge of Python is required. The programme FAQ "What background knowledge is necessary?" also lists awareness of common business processes and workflows in a corporate context (monitoring, reporting, ticketing, troubleshooting/debugging, quality testing, escalation) and of common corporate approaches to technology infrastructure and operations (governance, policy and protocol, version control, cloud architecture, CI/CD, DevSecOps practices, agile practices and tools). Microsoft also lists basic knowledge of AI and ML capabilities and of generative AI and pretrained large language models; familiarity with statistics is recommended. You need a license to Microsoft Azure (or a free trial version) and appropriate hardware; the page notes the free Azure trial is time limited and may expire before completion of the program.
Sources ↗
Microsoft Certified: AI Business Professional (Exam AB-730)
Exam AB-730 leads to Microsoft Certified: AI Business Professional, a Beginner-level certification for business users who use generative AI tools such as Microsoft 365 Copilot and agents at work, without building AI apps or coding. From October 20, 2026 the study guide measures four skill areas: generative AI fundamentals (25-30%), prompts and chats in Microsoft 365 Copilot (20-25%), business content and collaboration with Copilot (20-25%), and business outcomes with agents (20-25%). The proctored exam lasts 45 minutes and needs a score of 700. The captured pages do not say whether this certification expires. As shown in the United States on 13 October 2026, no exam price is displayed; Microsoft says the price depends on where the exam is proctored.
- Duration
- 45 minutes to complete the exam assessmentnot preparation time
- Level
- Beginner
- Format
- Proctored certification exam
- Credential
- certification
- Prerequisites
- No prerequisite certification is stated on the captured pages. Microsoft says candidates should have experience using generative AI-powered productivity tools such as Microsoft 365 Copilot and agents, be comfortable with core Microsoft 365 apps (Outlook, Word, Microsoft Teams, PowerPoint and Excel) and be familiar with common business processes; no app building or coding is required.
Sources ↗
- Duration : https://learn.microsoft.com/en-us/credentials/certifications/ai-business-professional/
- Official program page : https://learn.microsoft.com/en-us/credentials/certifications/ai-business-professional/
- Modules or exam domains : https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ab-730
- Credential details : https://learn.microsoft.com/en-us/credentials/certifications/renew-your-microsoft-certification-faq
- Credential details : https://learn.microsoft.com/en-us/credentials/support/credential-expiration-policy
- Credential details : https://learn.microsoft.com/en-us/credentials/support/view-use-share-certificates-achievements
- Cost terms : https://learn.microsoft.com/en-us/credentials/support/retake-policy
Generative AI for Data Scientists Specialization
The Generative AI for Data Scientists Specialization on Coursera is an intermediate-level program offered by IBM. Designed for existing and aspiring data professionals, the curriculum teaches students how to apply generative AI to data science workflows. Learners explore prompt engineering and tools like ChatGPT, IBM Watsonx, Prompt Lab, and Dust. The self-paced online program has headline estimates of under 1 month or 4 weeks to complete at 10 hours a week. The curriculum consists of 3 courses. Earning the shareable provider-issued course certificate requires completing the work. As shown in the United States on 13 October 2026, the program is taught in English.
- Duration
- under 1 month4 weeks to complete at 10 hours a week
- Level
- Intermediate level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The FAQ states 'No experience is necessary' but also notes 'Prior data science experience is helpful'.
Sources ↗
Product Management for AI & Data Science
365 Data Science's 'Product Management for AI & Data Science' is a basic-level online course instructed by Danielle Thé, designed to teach the full lifecycle of AI and data science projects. The 6-hour provider headline duration covers defining AI business opportunities, understanding machine learning versus deep learning, product ideation techniques, and managing data science teams. Earning the provider-issued course certificate requires completing the course and passing the associated course exams with a score of 60% or higher. The provider lists 7.5 CPE credits; however, acceptance depends on individual state boards. No prior experience is required, though 'Intro to AI' is recommended. Pricing observations in the United States on 13 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 6 hours (provider headline). Lessons (5 hours) and Practice exams (42 minutes) are listed separately.
- Level
- Basic
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: No prior experience or knowledge is required. Recommended advanced preparation: Intro to AI.
Sources ↗
ChatGPT at Work: Ethical and Secure ChatGPT Use
365 Data Science's 'ChatGPT at Work: Ethical and Secure ChatGPT Use' is a basic-level online course designed for leaders, managers, and teams. Instructed by Ned Krastev and Ivan Manov, the 2-hour provider headline duration covers generative AI evolution, ChatGPT risks, global regulations, and responsible adoption strategies. Earning the provider-issued course certificate requires completing the course and passing the associated course exam with a score of 60% or higher. The provider lists 4.5 CPE credits; acceptance depends on individual state boards. The required prerequisite is access to ChatGPT, with advanced preparation in Intro to ChatGPT and Generative AI recommended. Pricing observations in the United States on 14 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 2 hours (provider headline; module and exam timings listed separately)
- Level
- Basic
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required prerequisite: Access to ChatGPT. Advanced preparation: Intro to ChatGPT and Generative AI.
Sources ↗
- Duration : https://365datascience.com/courses/chatgpt-at-work-ethical-and-secure-chatgpt-use/
- Official program page : https://365datascience.com/courses/chatgpt-at-work-ethical-and-secure-chatgpt-use/
- Credential details : https://365datascience.com/certificates/
- Cost terms : https://365datascience.com/pricing/
Generative AI for Software Development Skill Certificate
The Generative AI for Software Development Skill Certificate on Coursera is a program offered by DeepLearning.AI. While the page lists a beginner level, the FAQ explicitly states intermediate knowledge of software development is necessary. Designed for software developers and engineers, the curriculum teaches students how to use generative AI in their workflows. Learners explore prompt engineering, pair programming with LLMs, code testing, and database development. The self-paced online program has a headline estimate of 4 weeks at 5 hours a week, and an FAQ estimate of about 5 hours per course. The curriculum consists of 3 courses. Earning the shareable provider-issued course certificate requires completing the work. As shown in the United States on 14 October 2026, the program is taught in English.
- Duration
- Headline estimate of 4 weeks at 5 hours a week. The FAQ estimates about 5 hours per course.
- Level
- Beginner level
- Format
- Flexible schedule, Learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The main page lists 'Beginner level' and 'Recommended experience', while the FAQ states 'Intermediate knowledge of software development' is necessary and familiarity with programming languages like Python, JavaScript, and C# will help.
Sources ↗
Generative AI for Software Developers Specialization
The Generative AI for Software Developers Specialization on Coursera is an intermediate-level program offered by IBM. Designed for existing and aspiring web, mobile, front-end, backend, and full stack developers, as well as DevOps and SREs, the curriculum teaches how to apply generative AI to software workflows. Learners explore prompt engineering and tools like ChatGPT, GitHub Copilot, and Google Gemini. The self-paced online program has headline estimates of 1 month or less, or 4 weeks to complete at 10 hours a week. The curriculum consists of 3 courses. Earning the shareable provider-issued course certificate requires completing the work. As shown in the United States on 14 October 2026, the program is taught in English.
- Duration
- 1 month or less4 weeks to complete at 10 hours a week
- Level
- Intermediate level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The FAQ states 'This Professional Certificate is open to anyone with any job and academic background', while the header lists 'Intermediate level' and 'Recommended experience'.
Sources ↗
Introduction to Amazon Bedrock
365 Data Science's 'Introduction to Amazon Bedrock' is a basic-level online course instructed by Anita Okoh. The 2-hour provider headline duration introduces developers to Amazon Bedrock, covering foundation models, programmatic access via Python and AWS SDK, and building serverless applications with AWS Lambda and API Gateway. Earning the provider-issued course certificate requires completing the course and passing the associated course exam with a score of 60% or higher. The provider lists 4 CPE credits; however, acceptance depends on individual state boards. The course requires a basic understanding of Python and familiarity with AWS. Pricing observations in the United States on 15 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 2 hours (provider headline). Lessons (1 hour) are explicitly listed. The course exam is 30 minutes.
- Level
- Basic
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Basic Understanding of Python, Familiarity with AWS.
Sources ↗
Generative Adversarial Networks (GANs) Specialization
The Generative Adversarial Networks (GANs) Specialization by DeepLearning.AI on Coursera is an intermediate-level program introducing image generation from foundational concepts to advanced techniques. The curriculum covers basic GANs using PyTorch, advanced DCGANs with convolutional layers, evaluating fidelity using the Fréchet Inception Distance (FID) method, detecting bias, and implementing state-of-the-art StyleGAN. Students also explore data augmentation, privacy preservation, Pix2Pix, and CycleGAN for image translation. The self-paced online program has a provider estimate of 2 months to complete at 10 hours a week. Earning the shareable certificate requires completing the 3-course series work. The program was reviewed in the United States on 15 October 2026.
- Duration
- 2 months to complete at 10 hours a week
- Level
- Intermediate level
- Format
- Flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- Expected background: working knowledge of AI, deep learning, and convolutional neural networks; intermediate Python skills; some experience with any deep learning framework (TensorFlow, Keras, or PyTorch); proficient in basic calculus, linear algebra, and statistics. Highly recommended: Deep Learning Specialization.
Sources ↗
IBM RAG and Agentic AI Professional Certificate
The IBM RAG and Agentic AI Professional Certificate on Coursera is an advanced-level program designed to equip learners with skills in generative AI. Instructed by IBM, the curriculum teaches students to use retrieval-augmented generation (RAG) and multi-agent systems to build intelligent applications. Learners gain hands-on experience integrating tools with AI agents, orchestrating workflows using LangChain and LangGraph, and utilizing frameworks like CrewAI and Model Context Protocol. The self-paced online program has a headline estimate of 8 weeks to complete at 3 hours a week, with another section estimating 3 months. Earning the shareable provider-issued course certificate requires completing the 10-course series and a final capstone project. As shown in the United States on 15 October 2026, the program is taught in English.
- Duration
- 8 weeks at 3 hours a week
- Level
- Advanced level
- Format
- Online, flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The provider requires working knowledge of Python programming and a fundamental knowledge of web development and AI concepts.
Sources ↗
Introduction to MLflow
365 Data Science's 'Introduction to MLflow' is an advanced-level online course instructed by Stefan Micic, designed for data scientists, ML engineers, and developers to learn end-to-end machine learning lifecycle management. The 1-hour provider headline duration covers tracking experiments, packaging reproducible projects, deploying models locally, and integrating MLflow into automated pipelines. Earning the provider-issued course certificate requires completing the course and passing the associated course exam with a score of 60% or higher. The provider lists 4 CPE credits; however, acceptance depends on individual state boards. A basic understanding of Python is required. Pricing observations in the United States on 15 October 2026 indicate platform subscription access rather than a fixed per-course fee.
- Duration
- 1 hour (provider headline). Lessons (2 hours) are listed separately.
- Level
- Advanced
- Format
- Online Course
- Credential
- Provider-issued course certificate
- Prerequisites
- Required: Basic Understanding of Python, Enthusiasm for Learning. Advanced preparation: None.
Sources ↗
IBM AI Enterprise Workflow Specialization
The IBM AI Enterprise Workflow Specialization on Coursera is an advanced-level program designed for existing data science practitioners seeking to build and deploy AI solutions in large enterprises. Instructed by IBM, the six-course curriculum covers data ingestion, exploratory data analysis, feature engineering, model training, and enterprise model deployment using tools like Python, Jupyter, Apache Spark, and IBM Cloud technologies. Learners gain hands-on experience through case studies focusing on a hypothetical streaming media company. The self-paced online program has a headline estimate of 2 months to complete at 10 hours a week, though an FAQ section estimates 35-40 hours of total study. Completing the program prepares learners for the IBM AI Enterprise Workflow V1 Data Science Specialist certification exam. As shown in the United States on 15 October 2026, the program is taught in English.
- Duration
- Headline: 2 months to complete at 10 hours a week. FAQ: The entire specialization will require 35-40 hours of study.
- Level
- Advanced level
- Format
- Flexible schedule, learn at your own pace
- Credential
- Provider-issued course certificate
- Prerequisites
- The provider explicitly requires a fundamental understanding of Linear Algebra, sampling, probability theory, probability distributions, descriptive and inferential statistical concepts, machine learning techniques and best practices, plus a practiced understanding of Python and data science packages (NumPy, Pandas, matplotlib, scikit-learn). Familiarity with IBM Watson Studio and the design thinking process is also required. An FAQ section further notes it is highly recommended to have at least a basic working knowledge of design thinking and Watson Studio prior to taking the course. Course 1 includes a Readiness Exam to test preparation.
Sources ↗
Large Language Model Operations (LLMOps) Specialization
The 'Large Language Model Operations (LLMOps) Specialization' by Duke University on Coursera is a beginner-level, 6-course program focused on deploying, managing, and optimizing large language models. Taught in English, the program covers generative AI techniques across platforms like Azure, AWS, Databricks, and local infrastructure. The curriculum includes over 20 coding projects to build hands-on experience, preparing learners for roles such as Machine Learning Engineer or Cloud Architect. It takes about 5 months to complete at 10 hours a week. Earning the shareable career certificate requires completing the coursework, though the exact mandatory assessment count is not specified. As shown in the United States on 15 October 2026, no exact subscription cost is provided, though financial aid is available.
- Duration
- 5 months to complete at 10 hours a week
- Level
- Beginner level
- Format
- 100% online, self-paced course
- Credential
- Provider-issued course certificate
- Prerequisites
- The source page displays a 'Recommended experience' label but does not detail which specific experience is recommended.
Sources ↗
Supply Chain Management: AI, Sustainability, and Resilience Strategies Program
Yale School of Management Executive Education offers this six-week online programme through GetSmarter for experienced supply chain leaders. It covers operational innovation, AI and IoT applications, resilience, responsible supply chains and transformation leadership. Weekly study combines self-paced materials with assignments, live sessions and discussions. The stated audience has a strong grasp of supply chains and at least a decade of relevant experience. Successful participants meeting the handbook requirements receive a digital certificate of participation.
- Price
- USD 2800As shown in the United States on 15 October 2026, tuition is USD 2,800. An alternative interest-free schedule shows two USD 1,400 payments due 19 January and 18 February 2027; the first payment is processed at checkout and the amounts and schedule are finalized there. These installments are not additional charges.
- Duration
- 6 weeks excluding orientation6-8 hours per week
- Format
- Online cohort with weekly self-paced work, live sessions, assignments and discussions
- Credential
- Official digital certificate of participation
- Prerequisites
- The page addresses current and aspiring supply chain leaders with a strong grasp of the supply chain life cycle and at least a decade of experience in warehousing, transportation, operations or logistics. This is the stated audience profile; a separate formal admissions process is not specified.
Sources ↗
- Price : https://www.getsmarter.com/products/yale-som-executive-education-supply-chain-management-ai-sustainability-and-resilience-strategies-program
- Duration : https://www.getsmarter.com/products/yale-som-executive-education-supply-chain-management-ai-sustainability-and-resilience-strategies-program
- Official program page : https://www.getsmarter.com/products/yale-som-executive-education-supply-chain-management-ai-sustainability-and-resilience-strategies-program
Creative AI Foundations Microcertificate (Online)
Harvard Extension School offers this two-course online graduate microcertificate in human-centered design and creative AI. Learners study design and prototyping of interactive digital experiences, including usability, accessibility and ethics. Enrollment begins by registering for a course without an application. Both courses must be completed for graduate credit with at least a B in each, within two years. At least one course must be taken in Fall 2026 or later. The credential can stand alone or contribute toward the specified graduate certificate and degree pathways.
- Duration
- 8 months to 2 yearscomplete two courses within two years
- Level
- Graduate
- Format
- Onlinetwo courses with flexible pacing
- Credential
- Creative AI Foundations Microcertificate
- Prerequisites
- No application is required to begin: register for the first course. To earn the credential, take both courses for graduate credit, earn at least B in each, and finish within two years. At least one course must be completed in Fall 2026 or later. Course-specific prerequisites are not established on this programme page. As observed on 15 October 2026, the next start term is Spring 2027 and course registration runs from 5 November 2026 through 7 January 2027. These enrollment dates are separate from the Fall 2026 credential rule and the two-year completion limit.
Sources ↗
AI Systems, Strategy, and Responsibility Program
Stanford Online and its Institute for Human-Centered Artificial Intelligence offer this on-demand programme for executives, leaders and professionals. Three required courses cover technical foundations, business applications and human-centered generative AI. Themes include agentic and multimodal systems, evaluation, transformation and responsible governance. Successful completion of the three courses earns a blockchain-verified Stanford Certificate of Completion. Learners can choose individual-course access or an All-Access plan.
- Price
- USD 3135As shown in the United States on 15 October 2026, All-Access is USD 3,135 for 365 days. Alternatively, individual courses are USD 1,045 each with 60 days to complete and 60 days of teaching-assistant email access. All-Access can be paid in installments of USD 1,254 immediately and USD 940.50 in one and two months. These are alternative payment routes, not added fees.
- Duration
- Headline: 9-14 hours per course and 34 hours for the certificateother workload statements differ
- Format
- 100% online, on-demand
- Credential
- Stanford Certificate of Completion in AI Systems, Strategy, and Responsibility Program
- Prerequisites
- The page addresses executives, leaders and professionals. It does not state formal academic or coding prerequisites; this is not a no-prerequisites policy.
Sources ↗
Fast & Efficient LLM Inference with vLLM
This short course from DeepLearning.AI and Red Hat follows an optimize, deploy and benchmark workflow for an open-source language model. Learners quantize a model with LLM Compressor, serve it with vLLM, and benchmark performance and quality using GuideLLM and lm-eval. The course covers GPU memory, continuous batching, PagedAttention and prefix caching. Python and basic LLM familiarity are recommended.
- Duration
- 1h38m listed course durationindividual activity estimates are rounded
- Level
- Intermediate
- Format
- Online course with video lessons and listed learning activities
- Credential
- Accomplishment with Pro
- Prerequisites
- Python and basic LLM concepts, including tokens, inference and GPU usage, are recommended.
Sources ↗
Agent Skills with Anthropic
DeepLearning.AI and Anthropic teach how to package reusable instructions as agent skills. Learners explore skill structure, progressive disclosure, pre-built and custom skills, then use them with Claude API, Claude Code and the Claude Agent SDK. Examples address coding, data analysis and research workflows, including the relationship between skills, tools, MCP and subagents. The page labels the course beginner and addresses AI builders.
- Duration
- 2h19m listed course durationindividual activity estimates are rounded
- Level
- Beginner
- Format
- Online course with video lessons and listed learning activities
- Credential
- Accomplishment with Pro
- Prerequisites
- The stated audience is AI builders extending agents with reusable workflows. Specific coding or academic admission prerequisites are not stated.
Sources ↗
Document AI: From OCR to Agentic Doc Extraction
DeepLearning.AI and LandingAI teach document processing from traditional OCR to agentic extraction. Learners work with layout detection, reading order and vision language models, then use LandingAI Agentic Document Extraction to produce structured Markdown and JSON. Examples integrate document extraction with RAG, AWS pipelines and a research-paper chatbot using Strands Agents. Basic Python familiarity is recommended.
- Duration
- 3h11m listed course durationindividual activity estimates are rounded
- Level
- Intermediate
- Format
- Online course with video lessons and listed learning activities
- Credential
- Accomplishment with Pro
- Prerequisites
- Basic familiarity with Python is recommended.
Sources ↗
Applications of Machine Learning in Medicine Program
Stanford Online offers this two-course programme through Stanford School of Medicine and Stanford Medicine Health Education. It teaches healthcare data foundations, model development, deployment and ethical considerations. Topics include clinical text, electronic phenotyping, time-series data, predictive models and deep learning. The self-paced programme addresses clinicians, researchers and data professionals; coding experience is helpful but not necessary. Successful completion of both courses earns a blockchain-verified Stanford Certificate of Achievement. Individual-course and All-Access enrollment routes have different access periods.
- Price
- USD 1425As shown in the United States on 15 October 2026, All-Access costs USD 1,425 with a full year for both courses and 365 days of teaching-assistant email access. Individual courses cost USD 715 each with 60 days to complete and 60 days of teaching-assistant email access. The page calls All-Access a one-year subscription, but does not establish automatic renewal or a recurring charge.
- Duration
- Headline: 10 hours per course and 20 hours for the certificatecredential text separately states a minimum of 60 hours
- Format
- 100% online, self-paced and on-demand
- Credential
- Stanford Certificate of Achievement in Applications of Machine Learning in Medicine
- Prerequisites
- A coding background is helpful but not necessary. The page does not establish other formal academic admission requirements. As checked on 15 October 2026, the embedded descriptions of both required courses, XMLPH110 and XMLPH210, require R/R Studio to complete homework assignments. Download instructions are included, and R/R Studio is free to download and use. This is a course-tool requirement, not a prior-coding admission requirement.
Sources ↗
AI Code Review
DeepLearning.AI and Qodo teach practices for AI code review and construction of a context-aware review agent. Learners review before opening a pull request, supply task and repository context, and prioritize findings by risk. Code examples build a context engine using embeddings and vector search, then combine specialized review agents. Python familiarity is helpful.
- Duration
- 1h4m listed course durationindividual activity estimates are rounded
- Level
- Intermediate
- Format
- Online course with video lessons and listed learning activities
- Credential
- Accomplishment with Pro
- Prerequisites
- Comfort with Python is helpful because learners build a context engine and review agents.
Sources ↗
Transformers in Practice
DeepLearning.AI and AMD offer a practical course on transformer behavior, internals and deployment. Three modules cover autoregressive generation, attention and model layers, then GPU inference and optimization. Visualizations, labs and quizzes address sampling, structured output, quantization, KV caching, flash attention and speculative decoding. Learners should understand basic neural network concepts and have experience using LLMs. Pro members can earn a course certificate; membership is a separate recurring access cost.
- Duration
- 11h1m listed course durationindividual activity estimates are rounded
- Level
- Intermediate
- Format
- Online course with video lessons and listed learning activities
- Credential
- Course certificate with Pro
- Prerequisites
- Learners should be comfortable using LLMs through an API or chat interface and understand basic neural network concepts such as weights, layers and training. Prior model-building from scratch is not required.
Sources ↗
Build and Train an LLM with JAX
DeepLearning.AI and Google teach a compact language-model workflow using JAX. Learners implement a MiniGPT-style model, prepare data, train and save it, and run inference through a chat interface. The course uses Flax/NNX, Grain, Optax and Orbax to illustrate architecture, loading, optimization and checkpointing. Python and basic machine learning familiarity are recommended.
- Duration
- 49m listed course durationindividual activity estimates are rounded
- Level
- Intermediate
- Format
- Online course with video lessons and listed learning activities
- Credential
- Accomplishment with Pro
- Prerequisites
- Familiarity with Python and basic machine learning concepts is recommended.
Sources ↗
Intro to Federated Learning
DeepLearning.AI and Flower Labs introduce federated model training with Flower and PyTorch. The listed lessons cover the training process, tuning, data privacy and bandwidth. The page places this introductory course within a two-part series; the later federated LLM fine-tuning topics described in the overview are not treated as additional lessons in this course. Python, machine learning and LLM familiarity are stated for the intended audience. Free beta access and Pro accomplishments have separate boundaries.
- Price
- FreeAs shown in the United States on 15 October 2026, the visible page offers course access free for a limited time during the platform beta. The end date is not stated. Pro accomplishments are separate; no free credential, perpetual free access or Pro membership price is inferred.
- Duration
- 1h18m listed course durationindividual activity estimates are rounded
- Level
- Beginner
- Format
- Online course with video lessons and listed learning activities
- Credential
- Accomplishment with Pro
- Prerequisites
- A basic background in Python and machine learning and an understanding of LLMs are stated for the audience.
Sources ↗
Red Teaming LLM Applications
DeepLearning.AI presents a beginner course on evaluating LLM application vulnerabilities with instructors from Giskard. Learners examine manual and automated red teaming, testing at scale, LLM-assisted assessments and a full assessment example. The focus is testing and improving LLM applications, rather than a guarantee of security or regulatory compliance. Basic Python knowledge is recommended. The page separately identifies free beta access and Pro accomplishments.
- Price
- FreeAs shown in the United States on 15 October 2026, the visible page offers course access free for a limited time during the platform beta. The end date is not stated. Pro accomplishments are separate; no free credential, perpetual free access or Pro membership price is inferred.
- Duration
- 1h39m listed course durationindividual activity estimates are rounded
- Level
- Beginner
- Format
- Online course with video lessons and listed learning activities
- Credential
- Accomplishment with Pro
- Prerequisites
- Basic Python knowledge is recommended.
Sources ↗
AI Prompting for Everyone
Andrew Ng teaches practical use of modern AI for finding information, brainstorming, writing, multimedia and simple application creation. Three modules address pretrained knowledge, web search and deep research; context, reasoning and critique; then images, applications and data analysis. No technical background is required. The course includes quizzes and practice activities. Pro members can earn a DeepLearning.AI Certificate of Completion; free content access does not include that credential.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states free users can access course content but receive no certificate. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified. The course FAQ separately quotes Pro at USD 30 per month billed monthly or USD 25 per month billed annually, as shown in the United States on 15 October 2026; taxes may apply. These are recurring access quotes, not a completion total or an explicitly listed annual charged amount.
- Duration
- 7h4m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Certificate of Completion
- Prerequisites
- No technical background or prerequisites are required.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/ai-prompting-for-everyone
- Official program page : https://www.deeplearning.ai/courses/ai-prompting-for-everyone
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Build with Andrew
Andrew Ng teaches beginners to build and customize browser applications by describing what they want to AI. Examples include a birthday-message application and a table-tennis game. Learners practice prompting, downloading an application, refining features and troubleshooting, then submit a final project and take a quiz. The course assumes no prior AI or coding knowledge. Free auditing includes videos and the forum; Pro adds assessments, project tools and a certificate after the required assessments.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states free users can access course content but receive no certificate. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified. The course FAQ separately quotes Pro at USD 30 per month billed monthly or USD 25 per month billed annually, as shown in the United States on 15 October 2026; taxes may apply. These are recurring access quotes, not a completion total or an explicitly listed annual charged amount.
- Duration
- 1h listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Certificate of Completion
- Prerequisites
- No prior knowledge of AI or coding is assumed.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/build-with-andrew
- Official program page : https://www.deeplearning.ai/courses/build-with-andrew
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Building AI Assistants with On-Device Memory
DeepLearning.AI and Qdrant teach an on-device memory system for an AI assistant. Learners store, retrieve, filter and delete text and image memories, add voice interaction, and recognize objects from examples without retraining. The course includes running the assistant locally and optional hybrid-memory material. Python familiarity is recommended. Pro completion recognition is an Accomplishment, not an official certificate.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h4m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python is recommended. The page says no specialized hardware is required and describes Mac, Windows and Linux use.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/building-ai-assistants-with-on-device-memory
- Official program page : https://www.deeplearning.ai/courses/building-ai-assistants-with-on-device-memory
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Building Adaptive AI Agents
DeepLearning.AI and Oracle teach three forms of agent adaptation: behavior, knowledge and the model itself. Learners turn agent traces into reusable skills with human approval, construct a code knowledge graph, and examine when model adaptation is useful. The course contrasts graph retrieval with keyword search. Python familiarity is recommended. Pro members who complete this short course can receive an Accomplishment.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h3m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python is recommended for the hands-on labs.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/building-adaptive-ai-agents
- Official program page : https://www.deeplearning.ai/courses/building-adaptive-ai-agents
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
AI Coding Workflows: From Cloud to Local
DeepLearning.AI and JetBrains compare cloud, hybrid and local AI coding workflows by rebuilding the same Python application. Lessons use Claude Code, focused subagents, smaller models, OpenCode, OpenRouter and LM Studio. The emphasis is evaluating workflow tradeoffs, not a universal promise of lower cost or better performance. Python and terminal familiarity are expected, and local-model lessons benefit from a capable machine.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h32m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Comfort with Python and terminal work is expected. The local-model lessons run best on a reasonably capable machine; a specific hardware minimum is not listed.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/ai-coding-workflows-from-cloud-to-local
- Official program page : https://www.deeplearning.ai/courses/ai-coding-workflows-from-cloud-to-local
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Fast LLM Inference with Cerebras
DeepLearning.AI and Cerebras explore how inference hardware and memory movement affect application design. Learners examine the Wafer-Scale Engine, compare hardware approaches, and build personalization and multi-tool workflows. A lesson also covers multi-agent coding practices. Python and LLM API familiarity are helpful. The course demonstrates latency-sensitive use cases; no independently measured hardware-performance claim is made here.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h41m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic familiarity with Python and calling an LLM API is helpful.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/fast-llm-inference-with-cerebras
- Official program page : https://www.deeplearning.ai/courses/fast-llm-inference-with-cerebras
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Voice for AI Agents and Applications
This DeepLearning.AI short course with Vocal Bridge teaches three voice integration patterns: voice inside an application, a voice layer on an existing agent, and voice as a tool. Learners work on an interactive game, agent integration and a demonstration calling workflow, then evaluate voice interactions. Basic Python familiarity is recommended; voice API experience is not required. The separate builder challenge is not part of the course credential.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h26m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic Python familiarity is recommended. No prior experience with voice APIs is required.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/voice-for-ai-agents-and-applications
- Official program page : https://www.deeplearning.ai/courses/voice-for-ai-agents-and-applications
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
AI Agents for Image and Video Generation
DeepLearning.AI and Google teach agents that generate, evaluate and refine images and video. Learners use image-text similarity, LLM judges and structured rubrics, build a brand-guided UI mockup agent, and create a multi-scene video agent. The course also packages workflows as reusable skills and uses Gemini CLI. Python and LLM API familiarity are recommended.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h34m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python and basic experience with LLM APIs are recommended.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/ai-agents-for-image-and-video-generation
- Official program page : https://www.deeplearning.ai/courses/ai-agents-for-image-and-video-generation
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Build Interactive Agents with Generative UI
DeepLearning.AI teaches interactive agent interfaces with CopilotKit and AG-UI. Lessons move from controlled components to declarative layouts and open interfaces, then a canvas application with shared state. Learners connect agents to a React frontend and explore MCP Apps. React, Python and basic agent-development familiarity are recommended despite the beginner course label.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h28m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Comfort with React and Python is recommended, along with basic familiarity with AI agents or LLM application development.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/build-interactive-agents-with-generative-ui
- Official program page : https://www.deeplearning.ai/courses/build-interactive-agents-with-generative-ui
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Building Multimodal Data Pipelines
This DeepLearning.AI short course with a Snowflake instructor teaches pipelines that turn images, audio and video into searchable text. Learners use transcription, OCR and semantic search, process video with vision language models, and build a multimodal RAG system over meeting recordings. Python, SQL and basic data engineering knowledge are recommended.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h1m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python, SQL queries and basic data engineering concepts is recommended.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/building-multimodal-data-pipelines
- Official program page : https://www.deeplearning.ai/courses/building-multimodal-data-pipelines
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Spec-Driven Development with Coding Agents
DeepLearning.AI and JetBrains teach specification-driven workflows for AI coding agents. Learners create a project constitution, specify and validate features, replan work, produce an MVP and apply the method to existing code. The final lessons package a custom workflow as a skill. Programming familiarity and experience with LLM coding tools are recommended.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h16m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic familiarity with a programming language and experience with LLM-based coding tools are recommended.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/spec-driven-development-with-coding-agents
- Official program page : https://www.deeplearning.ai/courses/spec-driven-development-with-coding-agents
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Efficient Inference with SGLang: Text and Image Generation
DeepLearning.AI, LMSys and RadixArk teach inference optimization with SGLang. Learners implement attention and a KV cache, extend reuse across requests with RadixAttention, and apply related caching and parallelism ideas to diffusion image generation. Python and basic language-model familiarity are recommended. The course covers caching implementation rather than a guaranteed deployment-speed improvement.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider help page states Short Courses are free; Accomplishments require a Pro subscription. This zero is scoped to free content access, not a credential-inclusive completion total. The captured membership page does not expose a numeric price in its visible text. External API, cloud, compute and tool costs are not quantified.
- Duration
- 1h19m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python and basic language-model concepts is recommended.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/efficient-inference-with-sglang-text-and-image-generation
- Official program page : https://www.deeplearning.ai/courses/efficient-inference-with-sglang-text-and-image-generation
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Vibe Coding 101 with Replit
DeepLearning.AI and Replit teach a structured approach to building with coding agents. Learners plan an SEO analyzer with a product requirements document and wireframe, debug and customize it, and build a national-park voting app with persistent storage. The course covers prompting, checkpoints, context and deployment using Replit. Coding and LLM prompting experience are helpful, and a free Replit account is required for completion. The page does not establish the full cost of external deployment or compute.
- Price
- FreeAs shown in the United States on 16 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h34m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Anyone can join; coding experience and LLM prompting background are helpful. A free Replit account is required to complete the course. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/vibe-coding-101-with-replit
- Official program page : https://www.deeplearning.ai/courses/vibe-coding-101-with-replit
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Long-Term Agentic Memory With LangGraph
DeepLearning.AI and LangChain teach long-term memory through a personal email-agent example. Learners build routing, writing and scheduling tools, then add semantic facts, episodic examples and procedural system prompts. Hot-path and background memory mechanisms support the conceptual framework. Python and basic LLM application knowledge are helpful. The outline includes an appendix, code examples and a graded quiz. Email handling is a course example, not a promise of reliable autonomous operation.
- Price
- FreeAs shown in the United States on 16 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h24m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Python familiarity and a basic understanding of LLM prompting and application development are helpful. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/long-term-agentic-memory-with-langgraph
- Official program page : https://www.deeplearning.ai/courses/long-term-agentic-memory-with-langgraph
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Event-Driven Agentic Document Workflows
DeepLearning.AI and LlamaIndex teach document workflows with branching, loops and concurrent execution. Learners parse a source document, build a RAG query engine, convert PDF form fields into questions and return structured answers. Human feedback through text and voice lets the agent revisit responses. Basic Python and object-oriented programming knowledge are expected. The outline includes code examples, an appendix and a graded quiz. Accuracy improvements are learning goals, not guaranteed results.
- Price
- FreeAs shown in the United States on 16 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h19m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic Python knowledge and a basic understanding of object-oriented programming are the stated learner background. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/event-driven-agentic-document-workflows
- Official program page : https://www.deeplearning.ai/courses/event-driven-agentic-document-workflows
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Build Apps with Windsurf’s AI Coding Agents
DeepLearning.AI and Windsurf introduce coding agents through debugging, multi-file refactoring and application development. Learners inspect how agents use tools, human actions and context, explore code search, update an older codebase and build a Wikipedia analysis application. Examples add caching, visualization and UI changes while addressing unexpected agent behaviour. Coding familiarity and basic LLM prompting knowledge are helpful. The course includes an appendix of prompts and repositories; external software costs are not quantified.
- Price
- FreeAs shown in the United States on 16 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h30m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Coding familiarity is the stated audience background; basic LLM prompting and AI-assisted application development knowledge are helpful. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/build-apps-with-windsurfs-ai-coding-agents
- Official program page : https://www.deeplearning.ai/courses/build-apps-with-windsurfs-ai-coding-agents
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Evaluating AI Agents
DeepLearning.AI and Arize AI teach systematic agent evaluation. Learners build an agent, collect traces, evaluate routing and skills, and assess trajectories with a convergence score. Code-based evaluators, LLM judges and human annotations support component and end-to-end assessment. Structured experiments compare changes to prompts, models and logic, with production monitoring discussed. Basic Python is expected; prompting familiarity is optional. The outline includes five named labs, resources and a graded quiz.
- Price
- FreeAs shown in the United States on 16 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 2h36m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic Python knowledge is the stated background. LLM prompting familiarity is helpful but not required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/evaluating-ai-agents
- Official program page : https://www.deeplearning.ai/courses/evaluating-ai-agents
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Attention in Transformers: Concepts and Code in PyTorch
DeepLearning.AI and StatQuest explain attention mechanisms and implement them in PyTorch. Learners connect token and positional embeddings to query, key and value matrices, work through self-attention and masked self-attention, and examine encoder-decoder and multi-head attention. Coding examples implement these operations as classes. Basic Python is the stated background. This is a focused model-foundations course, rather than a general AI-assisted software development programme.
- Price
- FreeAs shown in the United States on 16 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h16m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic Python knowledge is the stated learner background; the page does not list a separate formal mathematics prerequisite. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/attention-in-transformers-concepts-and-code-in-pytorch
- Official program page : https://www.deeplearning.ai/courses/attention-in-transformers-concepts-and-code-in-pytorch
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Multi-vector Image Retrieval
DeepLearning.AI and Qdrant teach image retrieval with patch-level embeddings. Learners begin with ColBERT text retrieval, implement ColPali for images, reduce memory use with quantization and pooling, and use MUVERA representations for search. They combine these techniques in a multimodal RAG pipeline. Python and vector-embedding familiarity are recommended. The outline includes an optional project and a graded quiz; Pro completion recognition is an Accomplishment.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. The page also states that additional quizzes and projects are included with Pro. No complete third-party API, software or compute budget is established. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h43m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python and vector embeddings is recommended. The course header marks its 1 graded assignment as Pro access. The page also states that additional quizzes and projects are included with Pro. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/multi-vector-image-retrieval
- Official program page : https://www.deeplearning.ai/courses/multi-vector-image-retrieval
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Building Coding Agents with Tool Execution
DeepLearning.AI and E2B teach coding agents that generate and execute Python, manage files and respond to errors. Learners compare execution environments, run code in isolated cloud sandboxes, and build data-analysis and full-stack application agents. Examples use Pandas, Gradio and Next.js. Python and LLM familiarity are expected; prior agent knowledge is helpful but optional. The course includes a project and graded quiz.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. The page also states that additional quizzes and projects are included with Pro. No complete third-party API, software or compute budget is established. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h21m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python and LLMs is expected. Basic understanding of AI agents is helpful but not required. The course header marks its 1 graded assignment as Pro access. The page also states that additional quizzes and projects are included with Pro. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/building-coding-agents-with-tool-execution
- Official program page : https://www.deeplearning.ai/courses/building-coding-agents-with-tool-execution
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Semantic Caching for AI Agents
DeepLearning.AI and Redis teach semantic caching that reuses responses to similar questions. Learners build a cache from scratch, implement it with Redis tools, measure hit rate, precision, recall and latency, and test threshold tuning, cross-encoders and LLM validation. They then integrate caching into an agent. Python, embeddings and basic LLM applications are expected. Performance depends on the application; the course is not a guaranteed cost-saving result.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h24m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python, embeddings and basic LLM applications is expected. Basic caching experience is helpful but not required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/semantic-caching-for-ai-agents
- Official program page : https://www.deeplearning.ai/courses/semantic-caching-for-ai-agents
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Design, Develop, and Deploy Multi-Agent Systems with CrewAI
DeepLearning.AI and CrewAI offer four modules on building, controlling, coordinating and deploying agents. Learners use tools, memory, guardrails, execution hooks, Crews and Flows, then add tracing, evaluation and production monitoring. Code-review assignments provide practical work, while industry conversations examine business applications. The course is labelled beginner and its FAQ addresses learners with Python experience. Pro completion provides a DeepLearning.AI certificate; free content access excludes that credential.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 7 graded assignments as Pro access. No complete third-party API, software or compute budget is established. The course FAQ separately quotes USD 30 per month billed monthly or USD 25 per month billed annually, as shown in the United States on 15 October 2026; taxes may apply. These recurring access quotes are not a completion total or an explicitly stated annual charged amount.
- Duration
- 13h8m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Certificate of Completion
- Prerequisites
- The FAQ addresses learners with Python experience; it does not specify a formal prerequisite or minimum Python level. The course header marks its 7 graded assignments as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/design-develop-and-deploy-multi-agent-systems-with-crewai
- Official program page : https://www.deeplearning.ai/courses/design-develop-and-deploy-multi-agent-systems-with-crewai
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Jupyter AI: AI Coding in Notebooks
Andrew Ng and Project Jupyter co-founder Brian Granger teach AI-assisted coding inside notebooks. Learners generate and explain code, provide documentation as context, and build a book research assistant using the Open Library API. Another workflow analyzes and visualizes stock-market data. Exercises and local setup instructions are included. No AI coding-tool experience is required; basic Python familiarity is helpful.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h14m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- No prior experience with AI coding tools is required. Basic Python familiarity is helpful. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/jupyter-ai-coding-in-notebooks
- Official program page : https://www.deeplearning.ai/courses/jupyter-ai-coding-in-notebooks
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Fine-tuning & RL for LLMs: Intro to Post-training
DeepLearning.AI and AMD teach LLM post-training across five modules. Topics include supervised fine-tuning, RLHF, reward modeling, PPO, GRPO and LoRA; evaluation and error analysis; data preparation; and production monitoring. Labs use AMD GPUs while the provider describes the methods as hardware-agnostic. Strong Python familiarity and basic LLM understanding are recommended. Pro completion provides a DeepLearning.AI certificate.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 11 graded assignments as Pro access. No complete third-party API, software or compute budget is established. The course FAQ separately quotes USD 30 per month billed monthly or USD 25 per month billed annually, as shown in the United States on 15 October 2026; taxes may apply. These recurring access quotes are not a completion total or an explicitly stated annual charged amount.
- Duration
- 13h19m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Certificate of Completion
- Prerequisites
- Strong familiarity with Python and a basic understanding of how LLMs work are recommended. The FAQ directs learners without programming experience to a beginner course such as Machine Learning Specialization. The course header marks its 11 graded assignments as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/fine-tuning-and-reinforcement-learning-for-llms-intro-to-post-training
- Official program page : https://www.deeplearning.ai/courses/fine-tuning-and-reinforcement-learning-for-llms-intro-to-post-training
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Governing AI Agents
DeepLearning.AI and Databricks teach governance across an agent’s lifecycle. Learners examine lifecycle management, risk, security and observability, then use Unity Catalog permissions, identities and anonymized views for an HR-analysis agent. Lessons cover evaluation and deployment with MLflow and a traceable endpoint. Basic Python familiarity is recommended. The outline labels its labs as videos and lists no separate code examples; it includes a graded quiz.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h30m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic Python familiarity is recommended. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/governing-ai-agents
- Official program page : https://www.deeplearning.ai/courses/governing-ai-agents
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Building Live Voice Agents with Google’s ADK
DeepLearning.AI and Google teach voice agents with the Agent Development Kit. Learners work with tools, sessions, state, memory and guardrails, then coordinate agents to research and produce a podcast using Gemini text-to-speech. The course reviews evaluation, persistent memory and deployment on Vertex AI. The page targets AI builders but states no formal prerequisites. Two separately listed orchestration activities are retained in the outline.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h25m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- The page does not state formal prerequisites or a minimum programming background. Its audience is AI builders extending agents beyond text. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/building-live-voice-agents-with-googles-adk
- Official program page : https://www.deeplearning.ai/courses/building-live-voice-agents-with-googles-adk
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Building and Evaluating Data Agents
DeepLearning.AI and Snowflake teach a data agent with a planner, executor and specialized sub-agents. Learners use LangGraph, connect a Cortex sub-agent to structured and unstructured data, and trace retrieval and responses. Evaluation covers relevance, groundedness, and alignment among the agent’s goal, plan and actions. Inline checks and prompt updates support improvement. Basic Python and object-oriented programming are recommended.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h59m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic knowledge of Python and object-oriented programming is recommended. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/building-and-evaluating-data-agents
- Official program page : https://www.deeplearning.ai/courses/building-and-evaluating-data-agents
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Build AI Apps with MCP Server: Working with Box Files
DeepLearning.AI and Box teach an invoice-processing application that evolves from local files to tools provided by the Box MCP server. Learners extract fields and create client reports, then build a multi-agent design with Google ADK and A2A communication. Basic Python is recommended; MCP, A2A and Box API experience are not required. Third-party service costs are not quantified by the captured course page.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 36m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic Python knowledge is recommended. No prior MCP, A2A or Box API experience is required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/build-ai-apps-with-mcp-server-working-with-box-files
- Official program page : https://www.deeplearning.ai/courses/build-ai-apps-with-mcp-server-working-with-box-files
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Knowledge Graphs for AI Agent API Discovery
DeepLearning.AI and SAP teach agents to discover APIs through a knowledge graph. Learners turn API specifications into a graph, add business-process relationships, and combine semantic retrieval with dependency information. An agent then discovers and executes APIs in process order using discovery, GET and POST tools. Basic Python knowledge is required. The course includes code examples and a graded quiz.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h14m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Basic Python knowledge is required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/knowledge-graphs-for-ai-agent-api-discovery
- Official program page : https://www.deeplearning.ai/courses/knowledge-graphs-for-ai-agent-api-discovery
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Agentic Knowledge Graph Construction
DeepLearning.AI and Neo4j teach collaborative agents that plan knowledge-graph construction. Using Google ADK, learners identify a user’s goal, suggest files, and propose schemas for structured data and unstructured text. They build and connect graphs from product, supplier and review data. Python familiarity is required; Cypher is optional. The course includes code examples and a graded quiz.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 3h8m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Python familiarity is required. Basic Cypher knowledge can help but is not required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/agentic-knowledge-graph-construction
- Official program page : https://www.deeplearning.ai/courses/agentic-knowledge-graph-construction
- Cost terms : https://www.deeplearning.ai/membership
- Cost terms : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Claude Code: A Highly Agentic Coding Assistant
DeepLearning.AI and Anthropic teach agentic coding workflows with Claude Code. Learners explore and extend a RAG chatbot, test and refactor code, use Git worktrees and GitHub integration, and configure hooks. Projects also turn an e-commerce notebook into a dashboard and a Figma mockup into a web application using MCP integrations. Python and Git familiarity are helpful. The outline labels ten lessons as videos and lists no separate code examples; a graded quiz is included.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 2h listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with Python and Git helps learners get the most from the course. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/claude-code-a-highly-agentic-coding-assistant
- Official program page : https://www.deeplearning.ai/courses/claude-code-a-highly-agentic-coding-assistant
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Pydantic for LLM Workflows
DeepLearning.AI teaches data validation for LLM applications using Pydantic. Learners validate user input, structure model responses, pass data models to LLM APIs and define tool-call parameters. A customer-support assistant provides the application context, and the outline includes a hands-on project, graded quiz and downloadable resources. Basic Python comfort is the stated audience background. The emphasis is validation across an application workflow rather than a guarantee that generated content is factually correct.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h50m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- The intended learner is comfortable with basic Python; no formal admission requirement is stated. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/pydantic-for-llm-workflows
- Official program page : https://www.deeplearning.ai/courses/pydantic-for-llm-workflows
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Post-training of LLMs
DeepLearning.AI presents post-training methods taught by Banghua Zhu of the University of Washington and Nexusflow. Learners examine supervised fine-tuning, direct preference optimization and online reinforcement learning, including data curation and reward design. Labs turn a base model into an instruction-following model, change a chat assistant’s identity and improve mathematical behaviour with GRPO. LLM familiarity is the stated audience background. This short course is separate from the longer Fine-tuning and RL introduction in the catalogue.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h26m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Familiarity with LLM basics is the stated audience background; a formal programming prerequisite is not specified. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/post-training-of-llms
- Official program page : https://www.deeplearning.ai/courses/post-training-of-llms
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Building with Llama 4
DeepLearning.AI and Meta introduce Llama 4’s architecture and application workflows. Learners use Maverick and Scout for text and image tasks, image grounding, long-context questions, prompt optimization and synthetic-data preparation. Examples use Meta’s API and Together.ai. The course page scopes Meta API access to a free limited preview for US-based developers; other service availability and costs are not established. The outline includes an Important Note, videos and a graded quiz.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h20m listed course duration
- Level
- Beginner
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Open to learners seeking hands-on Llama 4 experience; formal programming prerequisites are not stated. The page describes Meta’s official Llama API as a free limited preview for US-based developers; that is an API-access condition, not proof of unrestricted course-tool access. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/building-with-llama-4
- Official program page : https://www.deeplearning.ai/courses/building-with-llama-4
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
Orchestrating Workflows for GenAI Applications
DeepLearning.AI and Astronomer teach orchestration with Apache Airflow 3.0. Learners turn a notebook-based book-recommendation RAG prototype into separate ingestion and query pipelines, apply time-based and data-aware scheduling, and use dynamic task mapping. Retries, failure alerts and backfills support reliable operation. Python familiarity is expected, while Airflow experience is unnecessary. The outline retains an optional local-environment setup lesson, resources and a graded quiz.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 1h48m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- Python familiarity is expected; no prior Airflow experience is required. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/orchestrating-workflows-for-genai-applications
- Official program page : https://www.deeplearning.ai/courses/orchestrating-workflows-for-genai-applications
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial
DSPy: Build and Optimize Agentic Apps
DeepLearning.AI and Databricks teach DSPy’s signature and module programming model. Learners build a sentiment classifier and guessing game, inspect a travel-booking assistant with MLflow tracing, and optimize a Wikipedia RAG application using prompt tuning and few-shot examples. The reported accuracy improvement belongs to a course example, not a guaranteed outcome. No prior DSPy experience is required; a minimum Python level is not stated.
- Price
- FreeAs shown in the United States on 15 October 2026, the provider support page allows free content access, excluding certificates and Accomplishments. Zero applies only to content access, not a credential-inclusive total. The course header marks its 1 graded assignment as Pro access. No complete third-party API, software or compute budget is established. The course page describes free access as limited to the platform beta; no end date is stated. No numeric Pro subscription price is established by this course page or the visible membership capture.
- Duration
- 59m listed course duration
- Level
- Intermediate
- Format
- Online self-paced learning with video lessons and listed activities
- Credential
- DeepLearning.AI Accomplishment
- Prerequisites
- No prior DSPy knowledge or experience is required. The page does not specify a minimum Python level. The course header marks its 1 graded assignment as Pro access. Free content access does not establish access to every listed assessment or project.
Sources ↗
- Price : https://info.deeplearning.ai/knowledge-base/draft-understanding-certificates-and-accomplishments-in-deeplearning.ai-courses
- Duration : https://www.deeplearning.ai/courses/dspy-build-optimize-agentic-apps
- Official program page : https://www.deeplearning.ai/courses/dspy-build-optimize-agentic-apps
- Credential details : https://www.deeplearning.ai/membership
- Credential details : https://info.deeplearning.ai/knowledge-base/how-do-refunds-work-for-the-deeplearning.ai-pro-membership-free-trial