AI Agents in Python
Build autonomous LLM agents from scratch: tool use, the ReAct reasoning loop, memory, planning, RAG, multi-agent systems, reflection and guardrails. Every lesson runs real Python with a deterministic LLM stub.
Every lesson runs real code in your browser, checked the moment you submit. No installing anything, no setup, no waiting.
Start AI Agents in Python freeWhat this course covers
- What Is an AI Agent?
- The LLM Is the Brain
- Prompts and Roles: Steering the Brain
- Reading the Model's Decision
- Tools: Giving the Agent Hands
- Describing Tools in JSON: Function Calling
- Parsing Structured Output from LLMs
- The Tool-Calling Loop
- Build a Calculator Agent (End to End)
- ReAct: Reason + Act
- Looping Until the Final Answer
- Planning: Break a Goal into Steps
- Short-Term Memory: Conversation History
- Long-Term Memory: Save and Recall Facts
- RAG: Giving Agents Knowledge
- Similarity Search: Finding the Closest Meaning
- Multiple Agents Working Together
- Reflection: The Agent Checks Its Own Work
- Evaluating Your Agent: Golden Set Testing
- Guardrails: Keeping Agents Safe
- Capstone: A Research Assistant Agent
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