Course focus: AI Agents for Beginners is a Microsoft curriculum with 18 topic lessons and Python samples built around Microsoft Agent Framework and Microsoft Foundry Agent Service V2.
What you will learn: It covers agent use cases, frameworks, design patterns, tools, agentic RAG, trust, planning, multi-agent collaboration, context, memory, MCP and A2A, browser use, scalable deployment, local agents, and security.
Recommended order: If generative-AI basics are unfamiliar, finish a basic LLM course first. Then complete course setup and follow lessons 1 through 6 before choosing advanced protocol, browser, or deployment topics.
Before you begin: Python experience is useful. The primary samples require a Microsoft Foundry setup and Azure account; some examples mention alternative OpenAI-compatible providers.
Who it suits: Useful for developers who understand basic API calls and want to learn why an agent is more than a long prompt.
Important limits: This is not a no-code course, and production lessons still require independent study of identity, evaluation, observability, cost, and failure recovery. Never grant tools broader permissions than the lesson needs. Use test accounts, approval checkpoints, allowlists, and isolated environments for browser or code-execution agents.
Project and license: Repository content is provided under MIT; check the current LICENSE before reuse. Repository: https://github.com/microsoft/ai-agents-for-beginners
Break the goal into input, action, and output before adding review checkpoints.
Keep examples, failure conditions, and review criteria so the tutorial stays reusable.