Program comparison
Building vs. Evaluating AI Agents: Which 365 Data Science Course Fits Your Goals?
For a Python practitioner choosing hands-on agent construction or structured evaluation of AI-agent systems.
For Python practitioners looking to expand their skills into AI agent systems, 365 Data Science offers two self-paced courses with different curriculum priorities. AI Agents in Practice focuses on constructing agent workflows, whereas Evaluating AI Agents: From Metrics to Real-World Impact focuses on measuring and evaluating AI systems. Both list 2 hours of content, not elapsed completion time. The useful distinction is the work you want to practise: building agents with tools and memory, or evaluating their outputs and behavior.
Facts side by side
Swipe or scroll the table to compare both programs.
| Fact | AI Agents in Practice | Evaluating AI Agents: From Metrics to Real-World Impact |
|---|---|---|
| Price | 365 Data Science Self-Study — USD 36/month for course content, billed monthly at the regular priceOfficial source · checked | 365 Data Science Self-Study — USD 36/month for course content, billed monthly at the regular priceOfficial source · checked |
| Duration | 2 hours (Official course-page advertised content duration, not total completion time; catalog separately also2hours.)Official source · checked | 2 hours (Official course-page advertised content duration, not total completion time; catalog separately also2hours.)Official source · checked |
| Level | AdvancedOfficial source · checked | IntermediateOfficial source · checked |
| Credential | Course certificateOfficial source · checked | Course certificateOfficial source · checked |
| Format | Online self-paced courseOfficial source · checked | Online self-paced courseOfficial source · checked |
| 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 requiredOfficial source · checked | Working knowledge of Python (functions, dictionaries, basic libraries like pandas); Basic understanding of machine learning workflows; No prior experience with AI evaluation frameworks neededOfficial source · checked |
Provider-listed modules and exam domains
AI Agents in Practice
- Introduction To The Course — 4 min · Source
- Rapid Foundations: Agentic Systems In Practice — 29 min · Source
- Project 1: Job-Helper Agent (ReAct) — 30 min · Source
- Project 2: ReWOO Job-Helper Agent — 22 min · Source
- Project 3: Business-Idea Evaluator — 21 min · Source
- Course Project And Exam — 1540 min; Provider-listed exam or combined project/exam section; duration kept separate from advertised content hours. · Source
Evaluating AI Agents: From Metrics to Real-World Impact
- Welcome & Foundations — 8 min · Source
- Core Evaluation Principles — 17 min · Source
- Quantitative Metrics & Benchmarking — 13 min · Source
- Evaluating LLM-Powered Agents — 14 min · Source
- Mastering RAG System Evaluation — 19 min · Source
- Human-Centric Evaluation Approaches — 12 min · Source
- Ethical Considerations In AI Evaluation — 12 min · Source
- Practical Evaluation Workflows & Future Outlook — 10 min · Source
- Capstone Project & Course Conclusion — 4 min · Source
- Course Exam — 40 min; Provider-listed exam or combined project/exam section; duration kept separate from advertised content hours. · Source
What the credentials are
AI Agents in Practice
- Credential type
- Course certificate · 365datascience.com / ai-agents-in-practice
- Issuer
- 365 Data Science · 365datascience.com / ai-agents-in-practice
- Exam requirement
- Provider curriculum includes course exam; exact pass requirements not captured. · 365datascience.com / ai-agents-in-practice
Evaluating AI Agents: From Metrics to Real-World Impact
- Credential type
- Course certificate · 365datascience.com / evaluating-ai-agents-from-metrics-to-real-world-impact
- Issuer
- 365 Data Science · 365datascience.com / evaluating-ai-agents-from-metrics-to-real-world-impact
- Exam requirement
- Provider curriculum includes course exam; exact pass requirements not captured. · 365datascience.com / evaluating-ai-agents-from-metrics-to-real-world-impact
Who should skip these options
AI Agents in Practice
- Learners seeking an absolute beginner program, because the prerequisites list intermediate Python skills and a foundational understanding of large language models. · Source
- Students who want a flat, guaranteed completion price: regular access is USD 36 per month, and third-party API usage may cost extra. · Source
Evaluating AI Agents: From Metrics to Real-World Impact
- Learners looking for a foundational introduction to programming, as the course requires existing proficiency in Python functions, dictionaries, and pandas. · Source
- 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. · Source
- 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. · Source
Scope and Target Audience
AI Agents in Practice carries an Advanced badge and is intended for learners who already understand basic large language models and want to build systems that can plan and use tools. Its curriculum guides students through a ReAct job-helper agent, a ReWOO job-helper agent, and a business-idea evaluator. Evaluating AI Agents is listed as Intermediate and addresses developers, product managers, and researchers. It covers quantitative metrics, RAG system evaluation, human-centric approaches, and ethical considerations. Its practical work includes Python metrics and retriever-evaluation exercises, so evaluation here is not a nontechnical alternative to building.
Prerequisites and Technical Demands
Both programs require Python knowledge, but their technical assumptions differ. The practice course asks for intermediate Python skills, comfort with notebooks, and a foundational grasp of LLM concepts such as prompts and tokens. If you are not comfortable writing functions or managing data structures, build those fundamentals first. The evaluation course requires working knowledge of Python and basic machine learning workflows, but does not require prior experience with AI evaluation frameworks. Choose by the stated prerequisites and curriculum rather than treating either short course as an introduction to programming.
Time Commitment and Cost
365 Data Science advertises each course as containing 2 hours of content. That is not a promise that exercises, projects and assessment fit inside two hours. Evaluating AI Agents separately lists a 40-minute exam; the practice course lists a combined Course Project and Exam section, not a standalone exam duration. At the regular price checked on 9 September 2026, both are included in Self-Study at USD 36 for one month of access. This is an access payment, not a guaranteed total cost to finish. The practice curriculum also includes funding an OpenAI API account; additional usage costs are not quantified in the saved source.
Bottom line
Choose AI Agents in Practice when your immediate goal is to work through agent construction using ReAct and ReWOO, provided you meet its Python and LLM prerequisites. Choose Evaluating AI Agents when you want to practise defining metrics, assessing RAG components, or organizing human feedback and responsible evaluation. Both have practical curricula, but neither a shared monthly access price nor the same advertised content hours makes them interchangeable. Their project and evaluation emphasis is more useful for this decision than the headline duration.
Which to choose if…
AI Agents in Practice
Choose AI Agents in Practice if you want to build ReAct and ReWOO agent workflows and already have intermediate Python and foundational LLM knowledge.
Evaluating AI Agents: From Metrics to Real-World Impact
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.
Alternatives in the registry
Related by topic or level.
- AI Agent ArchitecturePrice: 365 Data Science Self-Study — USD 36/month for course content, billed monthly at the regular priceOfficial source · checked Duration: 2 hours (Official course-page advertised content duration, not total completion time; catalog separately also2hours.)Official source · checked
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Official pages and editorial sources
- AI Agents in Practice — official page ↗
- Evaluating AI Agents: From Metrics to Real-World Impact — official page ↗
Editorial checked . No commercial relationship is documented for this comparison.