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Vanderbilt University · on Coursera

AI Agents and Agentic AI with Python & Generative AI

Beginner 10 hours English University CertificateFREE
SkillsAI agentsAgentic AIPythonGenerative AILLM integrationAgent design

Is this course right for you?

Our take
Also from Dr Jules White at Vanderbilt, this Coursera course builds AI agents in Python from the ground up — not by wiring an existing framework together, but by understanding how agents actually work.

Good for: Understanding how AI agents work by building them in Python.

Skip if: You cannot code Python or just want to use a framework.

That foundational, hands-on angle is the whole point: it suits Python coders who want genuine understanding rather than framework recipes, and it's a poor fit if you can't code or you just want to plug into a ready-made framework. Audit it free on Coursera (certificate on a subscription about $49/month or Coursera Plus, financial aid available); running your agents against model APIs is billed separately by the provider. Agentic AI moves fast, so check it reflects current tools (as of 2026).

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About this course

AI Agents and Agentic AI with Python & Generative AI is a from-the-ground-up course in building AI agents in Python — not wiring together an existing agent framework, but understanding how agents actually work. Dr. Jules White's GAME framework (Goals, Actions, Memory, Environment) structures the course around the core components every working agent needs.

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Instructor

JW
Jules White
Coursera instructor

Dr. Jules White is a professor at Vanderbilt University and one of Coursera's most-enrolled instructors for practical generative AI and agent-building courses.

Frequently asked questions

Yes — basic Python is the one real prerequisite. The course has you build AI agents in Python, so you should be comfortable with fundamentals like functions and working with libraries. You do not need prior AI or machine-learning knowledge, since it focuses on wiring language models into agents rather than training models. But this is genuinely a coding course, not a conceptual overview.

Notably, it has you build an agent framework yourself rather than leaning on an off-the-shelf one. The idea, from Vanderbilt's Dr Jules White, is that constructing each component — the agent loop, tool integration, safety patterns — from scratch gives you a deep understanding of how agents actually work, so you are not just calling a library you do not understand. That understanding then transfers to frameworks like LangChain later.

Building AI agents that can act on their own: the agent loop, integrating tools and APIs so agents can do real tasks, multi-agent collaboration, and design principles for making agents reliable. It also emphasises safety and trustworthiness — staged execution, reversible actions — and practical trade-offs between token cost, speed, and predictability, which matters because agentic systems can otherwise rack up API costs or behave unpredictably.

Likely small ones. Agents call large-language-model APIs, which charge by usage, so running the course projects can incur modest API costs — usually a few dollars if you are careful, and the course itself stresses managing token spend. You can keep it low with lighter models and careful testing, but budget a little for API credit beyond any subscription for the course itself.

You can audit it on Coursera to watch the lessons at no cost; the graded work and certificate need a subscription, with financial aid available. Remember the LLM API usage is a separate, usage-based cost regardless of how you take the course. Auditing suits you if you want to learn the concepts and follow along, with the paid track adding graded feedback and the credential.
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