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microsoft/ai-agents-for-beginners

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TLDR

A free 12-lesson Microsoft course teaching how to build AI agents, programs that autonomously plan and execute multi-step tasks using tools and external data.

Mindmap

mindmap
  root((repo))
    What it does
      Teaches AI agents
      Multi-step planning
      Tool integration
    Key concepts
      Agent perception
      Decision making
      RAG retrieval
      Multi-agent systems
    Learning format
      Written lessons
      Video tutorials
      Python code examples
    Tech stack
      Python
      Jupyter Notebooks
      Azure services
    Use cases
      Build autonomous systems
      Web automation
      Task planning
    Audience
      Python developers
      AI beginners
      Hands-on learners

Things people build with this

USE CASE 1

Learn how to build autonomous AI agents that can plan and execute multi-step tasks without human intervention.

USE CASE 2

Create web automation tools that browse the web, gather information, and take actions based on goals you specify.

USE CASE 3

Develop systems where multiple AI agents collaborate together to solve complex problems.

USE CASE 4

Understand how to integrate external tools, APIs, and data sources into AI agent workflows.

Tech stack

PythonJupyter NotebookAzureMicrosoft Agent Framework

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Azure account and API keys for LLM/agent services; Jupyter environment setup needed.

Use freely for any purpose including commercial, as long as you keep the copyright notice.

In plain English

This is a free, structured 12-lesson course created by Microsoft that teaches people how to build AI agents from scratch. An AI agent is a program that can take a sequence of actions autonomously, for example, browsing the web, running code, or calling external services, in order to accomplish a goal that you give it in plain language. Agents go beyond simple question-and-answer AI by being able to plan, make decisions, and use tools to complete multi-step tasks. The course covers the fundamentals of how agents work, including how they perceive their environment, how they plan sequences of actions, how they use tools and external data sources (a technique called Retrieval-Augmented Generation, or RAG), and how multiple agents can collaborate in a multi-agent system. Each lesson includes a written explanation, a short video, and working Python code examples that you can run yourself. The code examples use Microsoft's own agent development tools, the Microsoft Agent Framework and Azure AI Foundry Agent Service, which require an Azure account. Some lessons also include examples compatible with other AI providers. The content is available in over 50 languages through automated translations. You would use this course if you are new to AI agents and want a practical, hands-on introduction backed by real working code, rather than just theory. It is aimed at developers who already have some familiarity with Python but are new to the concept of autonomous AI systems. The tech stack is Python, presented through Jupyter Notebooks (interactive documents that combine code and explanations in the same file). Running the examples fully requires an Azure subscription for access to Microsoft's cloud AI services.

Copy-paste prompts

Prompt 1
Walk me through the first lesson of this AI agents course and show me how to set up a basic agent using the Microsoft Agent Framework.
Prompt 2
I want to build an agent that can search the web and summarize results. Which lesson in this course covers tool integration and how do I implement it?
Prompt 3
Show me the Python code example for a multi-agent system from this course and explain how the agents communicate with each other.
Prompt 4
How do I use Retrieval-Augmented Generation (RAG) in an AI agent? Point me to the relevant lesson and code example.
Prompt 5
I have an Azure account. Walk me through setting up and running one of the working code examples from this course.
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