365 AI Agents in Practice vs Evaluating AI Agents

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Decision fact	AI Agents in Practice	Evaluating AI Agents: From Metrics to Real-World Impact
Dated US-view price and payment scope	USD 36. One month of Self-Study access at regular monthly price. Not total cost to finish; third-party usage may cost extra. Official source · 2026-09-09	USD 36. One month of Self-Study access at regular monthly price. Not total cost to finish; third-party usage may cost extra. Official source · 2026-09-09
Listed workload or exam sitting	2 hours Official course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026. Official source · 2026-09-09	2 hours Official course-page advertised content duration, not total completion time; the 365 course catalog also showed 2 hours of content on 3 October 2026. Official source · 2026-09-09
Recorded level and format	Advanced; Online self-paced course Official source · 2026-09-09 Official source · 2026-09-09	Intermediate; Online self-paced course Official source · 2026-09-09 Official source · 2026-09-09
Award and assessment conditions	Observation 2026-09-09: Course certificate, issued by 365 Data Science. Provider curriculum includes course exam; exact pass requirements not captured. Certificate expiry and renewal are unstated. Official source · 2026-09-09	Observation 2026-09-09: Course certificate, issued by 365 Data Science. Provider curriculum includes course exam; exact pass requirements not captured. Certificate expiry and renewal are unstated. Official source · 2026-09-09
Preparation and audience limits	As recorded on 2026-09-09: 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 Learners seeking an absolute beginner program, because the prerequisites list intermediate Python skills and a foundational understanding of large language models.; Students who want a flat, guaranteed completion price: regular access is USD 36 per month, and third-party API usage may cost extra. Official source · 2026-09-09	Preparation observed 2026-09-09: Working knowledge of Python (functions, dictionaries, basic libraries like pandas); Basic understanding of machine learning workflows; No prior experience with AI evaluation frameworks needed Boundary observed 2026-09-09: Learners looking for a foundational introduction to programming, as the course requires existing proficiency in Python functions, dictionaries, and pandas. Boundary observed 2026-09-09: Individuals seeking completely free access to the full curriculum, because the reviewed minimum plan is a paid Self-Study subscription at USD 36 per month regular. Boundary observed 2026-09-09: Students who want to build AI models from scratch, as the curriculum focuses on evaluating and benchmarking existing systems like chatbots, classifiers, and retrieval-augmented generation pipelines. Official source · 2026-09-09
Inventory and assessment-time interpretation	Listed entries: Introduction To The Course (4 min); Rapid Foundations: Agentic Systems In Practice (29 min); Project 1: Job-Helper Agent (ReAct) (30 min); Project 2: ReWOO Job-Helper Agent (22 min); Project 3: Business-Idea Evaluator (21 min); Course Project And Exam (1540 min). Computed allocation: 1646 minutes across listed entries. The separately named assessment subset is 0 minutes out of 1646 listed minutes (0%). This does not mean there is no assessment work. The combined project/exam entry remains in the full denominator, but its assessment time cannot be separated. Module observations: 2026-09-09. The Course Project And Exam entry alone lists 1540 minutes, while the other five entries together list 106 minutes (1646 minus 1540). That large combined block makes the two-hour content headline unsuitable as a combined project-and-exam estimate. The stored figures do not establish how that block divides between project practice and the exam, how many sessions it takes, or how many subscription months a learner needs. Official source · 2026-09-09	Listed entries: Welcome & Foundations (8 min); Core Evaluation Principles (17 min); Quantitative Metrics & Benchmarking (13 min); Evaluating LLM-Powered Agents (14 min); Mastering RAG System Evaluation (19 min); Human-Centric Evaluation Approaches (12 min); Ethical Considerations In AI Evaluation (12 min); Practical Evaluation Workflows & Future Outlook (10 min); Capstone Project & Course Conclusion (4 min); Course Exam (40 min). Computed allocation: 149 minutes across listed entries. Separately named assessments total 40 minutes, 26.8% of 149 listed minutes (40 / 149 x 100, rounded to one decimal). Module observations: 2026-09-09. Official source · 2026-09-09

Agent-course entry arithmetic converts an hour to sixty minutes. Assessment percentages use all numeric entry minutes as the denominator; only separately named exams, quizzes or assessments enter the numerator, leaving combined project/exam time inseparable. The agent inventories do not time individual study effort or separate video from reading.

See AI Agents in Practice at 365 Data Science See Evaluating AI Agents: From Metrics to Real-World Impact at 365 Data Science

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Provider-listed modules and exam domains

AI Agents in Practice

Introduction To The Course · 4 min · ^[2]
Rapid Foundations: Agentic Systems In Practice · 29 min · ^[2]
Project 1: Job-Helper Agent (ReAct) · 30 min · ^[2]
Project 2: ReWOO Job-Helper Agent · 22 min · ^[2]
Project 3: Business-Idea Evaluator · 21 min · ^[2]
Course Project And Exam · 1540 min; Provider-listed exam or combined project/exam section; duration kept separate from advertised content hours. · ^[2]

Evaluating AI Agents: From Metrics to Real-World Impact

Welcome & Foundations · 8 min · ^[3]
Core Evaluation Principles · 17 min · ^[3]
Quantitative Metrics & Benchmarking · 13 min · ^[3]
Evaluating LLM-Powered Agents · 14 min · ^[3]
Mastering RAG System Evaluation · 19 min · ^[3]
Human-Centric Evaluation Approaches · 12 min · ^[3]
Ethical Considerations In AI Evaluation · 12 min · ^[3]
Practical Evaluation Workflows & Future Outlook · 10 min · ^[3]
Capstone Project & Course Conclusion · 4 min · ^[3]
Course Exam · 40 min; Provider-listed exam or combined project/exam section; duration kept separate from advertised content hours. · ^[3]

Choose the problem you need to solve

A working agent and a well-evaluated agent are different outcomes. Building a workflow can expose implementation gaps; evaluating it can expose uncertainty about what counts as a good result. Use the gap in your current work to choose between these scopes.

The courses can complement one another without creating a required purchase sequence. Their level labels are preparation context, not a scored ranking, and neither shared access pricing nor a similar headline duration establishes the same complete learning commitment.

Which to choose if…

Choose AI Agents in Practice when

You already know Python and LLM basics and want to build tool-using, multi-step workflows through the job-helper and business-idea examples.

Choose Evaluating AI Agents: From Metrics to Real-World Impact when

You want to define success measures, evaluate retrieval and agent outputs, and combine quantitative checks with human judgement.

The verdict

Winner

Depends on your learning goal

Score

AI Agents in Practice: 9.4 / 10 (3 of 5 criteria)
Evaluating AI Agents: From Metrics to Real-World Impact: 9.4 / 10 (3 of 5 criteria)

Five-criterion calculation
Criterion	Weight	AI Agents in Practice	Evaluating AI Agents: From Metrics to Real-World Impact
Scope match to the reader profile	2	2 / 2Introduction To The Course; Rapid Foundations: Agentic Systems In Practice; Project 1: Job-Helper Agent (ReAct); Project 2: ReWOO Job-Helper Agent; Project 3: Business-Idea Evaluator; Course Project And Exam ^[2]Coverage includes ReAct and ReWOO agent projects and a business-idea evaluator.	2 / 2Welcome & Foundations; Core Evaluation Principles; Quantitative Metrics & Benchmarking; Evaluating LLM-Powered Agents; Mastering RAG System Evaluation; Human-Centric Evaluation Approaches; Ethical Considerations In AI Evaluation; Practical Evaluation Workflows & Future Outlook; Capstone Project & Course Conclusion; Course Exam ^[3]Coverage includes quantitative metrics, RAG evaluation, human evaluation and ethics.
Credential features	2	not scored · Source-backed credential fields have not yet been established; the criterion is omitted for both programs.	not scored · Source-backed credential fields have not yet been established; the criterion is omitted for both programs.
Cost for the stated payment scope	1.5	2.0 / 2USD 36 · one month of access on Self-Study at the regular price ^[1]Prices differing by strictly less than 10% of the lower price tie at 2; otherwise 2 × lower price / this price.	2.0 / 2USD 36 · one month of access on Self-Study at the regular price ^[1]Prices differing by strictly less than 10% of the lower price tie at 2; otherwise 2 × lower price / this price.
Official preparation or completion hours	1	not scored · Comparable official preparation or completion estimates on the same basis are unavailable; listed content or track hours are not scored.	not scored · Comparable official preparation or completion estimates on the same basis are unavailable; listed content or track hours are not scored.
Entry requirements	0.5	1 / 2Intermediate 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 ^[2]	1 / 2Working knowledge of Python (functions, dictionaries, basic libraries like pandas); Basic understanding of machine learning workflows; No prior experience with AI evaluation frameworks needed ^[3]

AI Agents in Practice: earned 7.50 of 8.0 eligible weighted points. 7.50 / 8.0 × 10 = 9.4.

Evaluating AI Agents: From Metrics to Real-World Impact: earned 7.50 of 8.0 eligible weighted points. 7.50 / 8.0 × 10 = 9.4.

Best for
Best for agent construction	AI Agents in PracticeThe curriculum includes ReAct and ReWOO job-helper projects. ^[2]
Best for evaluation practice	Evaluating AI Agents: From Metrics to Real-World ImpactThe curriculum includes quantitative metrics and RAG system evaluation. ^[3]

Why

AI Agents in Practice covers Project 1: Job-Helper Agent (ReAct) and Project 2: ReWOO Job-Helper Agent; Evaluating AI Agents: From Metrics to Real-World Impact covers Quantitative Metrics & Benchmarking and Mastering RAG System Evaluation. ^[2] · ^[3]
Payment scope: AI Agents in Practice: USD 36 for one month of access on Self-Study at the regular price versus Evaluating AI Agents: From Metrics to Real-World Impact: USD 36 for one month of access on Self-Study at the regular price. This compares access payments, not the cost of completing a program. ^[1]
AI Agents in Practice specifies basic knowledge; Evaluating AI Agents: From Metrics to Real-World Impact specifies basic knowledge. ^[2] · ^[3]

Choose AI Agents in Practice if you want to build ReAct and ReWOO agent workflows and already have intermediate Python and foundational LLM knowledge.

Choose Evaluating AI Agents: From Metrics to Real-World Impact if you have Python and basic machine learning knowledge and want to practise metrics, RAG evaluation and human-feedback methods.

Confidence

High · 0 of 14 used facts need rechecking or are older than 60 days, calculated as of 11 September 2026.

Programme pages and official options

AI Agents in Practice Read the programme profile
Evaluating AI Agents: From Metrics to Real-World Impact Read the programme profile

Sources

Editorial checked 2026-09-11.

365datascience.com/pricing/ · checked 2026-09-09
365datascience.com/courses/ai-agents-in-practice/ · checked 2026-09-09
365datascience.com/courses/evaluating-ai-agents-from-metrics-to-real-world-impact/ · checked 2026-09-09
365datascience.com/courses/ai-agent-architecture/ · checked 2026-09-09
365datascience.com/courses/build-conversational-ai-memory-with-langgraph/ · checked 2026-09-09
365datascience.com/courses/introduction-to-vector-databases-with-pinecone/ · checked 2026-09-09
365datascience.com/courses/ai-agents-in-practice/
365datascience.com/courses/evaluating-ai-agents-from-metrics-to-real-world-impact/
365datascience.com/courses/ai-agents-in-practice/ · checked 2026-09-11
365datascience.com/courses/evaluating-ai-agents-from-metrics-to-real-world-impact/ · checked 2026-09-11
365datascience.com/pricing/ · checked 2026-09-11

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Building agents or evaluating their behaviour

Dated facts side by side

Provider-listed modules and exam domains

AI Agents in Practice

Evaluating AI Agents: From Metrics to Real-World Impact

Choose the problem you need to solve

Which to choose if…

Choose AI Agents in Practice when

Choose Evaluating AI Agents: From Metrics to Real-World Impact when

Programme pages and official options

Other documented options

Sources

Dated facts side by side

Provider-listed modules and exam domains

AI Agents in Practice

Evaluating AI Agents: From Metrics to Real-World Impact

Choose the problem you need to solve

Which to choose if…

Choose AI Agents in Practice when

Choose Evaluating AI Agents: From Metrics to Real-World Impact when

Programme pages and official options

Other documented options

Sources

Program Change Monitor · every two weeks