AI Agents course syllabus
Follow the lessons in order — each one builds on the last. Tick them off as you go.
- What Are AI Agents? Agentic AI Explained What an AI agent is, how agentic AI differs from a chatbot or a fixed workflow, and when an agent is (and is not) the right tool. 4 min
- Tool Calling (Function Calling) Explained How LLMs call functions: tool schemas, the request → tool_use → tool_result cycle, and how to design tools a model uses well. 4 min
- Build an AI Agent from Scratch in Python Write a working AI agent in about 60 lines of Python — tools, the agent loop, stop reasons, errors and a step limit. 6 min
- Agent Memory, Planning & Reflection Short-term vs long-term agent memory, planning patterns like ReAct and plan-and-execute, and self-checking with reflection. 4 min
- Multi-Agent Systems, Evaluation & Safety Orchestrator–worker multi-agent designs, how to evaluate agents, and the guardrails every production agent needs. 4 min
- AI Agents Interview Questions Common agentic AI interview questions — tool calling, agent loops, memory, multi-agent design and safety — with clear answers. 4 min
AI Agents FAQ
Is this AI Agents tutorial free?
Yes. All 6 AI Agents lessons are free to read online with no sign-up. Each one includes working code examples you can copy and run.
Is AI Agents good for beginners?
Yes. The tutorial starts with "What Are AI Agents? Agentic AI Explained" and builds up one concept at a time, so you don't need any prior AI Agents experience — just follow the lessons in order.
How long does it take to learn AI Agents?
Reading all 6 lessons takes about 1 hour. Most learners need a few weeks of hands-on practice alongside the lessons to feel confident using AI Agents on real projects.
What should I learn after AI Agents?
Good next topics are Artificial Intelligence, Deep Learning, LLM Fine-Tuning, Generative AI. The AI Engineer Roadmap shows the full order.