This course has 11 lessons covering the fundamentals of building AI Agents. Each lesson covers its own topic so start wherever you like!
There is multi-language support for this course. Go to our available languages here.
If this is your first time building with Generative AI models, check out our Generative AI For Beginners course, which includes 21 lessons on building with GenAI.
Don't forget to star (🌟) this repo and fork this repo to run the code.
Each lesson in this course includes code examples, which can be found in the code_samples folder. You can fork this repo to create your own copy.
The code example in these exercises, utilize Azure AI Foundry and GitHub Model Catalogs for interacting with Language Models:
- Github Models - Free / Limited
- Azure AI Foundry - Azure Account Required
This course also uses the following AI Agent frameworks and services from Microsoft:
For more information on running the code for this course, go to the Course Setup.
Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request
If you get stuck or have any questions about building AI Agents, join our Azure AI Foundry Community Discord
If you have product feedback or errors whilst building visit our Azure AI Foundry Developer Forum
- A written lesson located in the README and a short video
- Python code samples supporting Azure AI Foundry and Github Models (Free)
- Links to extra resources to continue your learning
| Lesson | Text & Code | Video | Extra Learning |
|---|---|---|---|
| Intro to AI Agents and Agent Use Cases | Link | Video | Link |
| Exploring AI Agentic Frameworks | Link | Video | Link |
| Understanding AI Agentic Design Patterns | Link | Video | Link |
| Tool Use Design Pattern | Link | Video | Link |
| Agentic RAG | Link | Video | Link |
| Building Trustworthy AI Agents | Link | Video | Link |
| Planning Design Pattern | Link | Video | Link |
| Multi-Agent Design Pattern | Link | Video | Link |
| Metacognition Design Pattern | Link | Video | Link |
| AI Agents in Production | Link | Video | Link |
| AI Agents with MCP | Link | Link |
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Thanks to Shivam Goyal for contributing important code samples demonstrating Agentic RAG.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
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