AI Agents for Beginners - A Course
A course teaching everything you need to know to start building AI Agents
🌐 Multi-Language Support
Supported via GitHub Action (Automated & Always Up-to-Date)
Arabic | Bengali | Bulgarian | Burmese (Myanmar) | Chinese (Simplified) | Chinese (Traditional, Hong Kong) | Chinese (Traditional, Macau) | Chinese (Traditional, Taiwan) | Croatian | Czech | Danish | Dutch | Estonian | Finnish | French | German | Greek | Hebrew | Hindi | Hungarian | Indonesian | Italian | Japanese | Kannada | Khmer | Korean | Lithuanian | Malay | Malayalam | Marathi | Nepali | Nigerian Pidgin | Norwegian | Persian (Farsi) | Polish | Portuguese (Brazil) | Portuguese (Portugal) | Punjabi (Gurmukhi) | Romanian | Russian | Serbian (Cyrillic) | Slovak | Slovenian | Spanish | Swahili | Swedish | Tagalog (Filipino) | Tamil | Telugu | Thai | Turkish | Ukrainian | Urdu | Vietnamese
Prefer to Clone Locally?
This repository includes 50+ language translations which significantly increases the download size. To clone without translations, use sparse checkout:
Bash / macOS / Linux:
git clone --filter=blob:none --sparse https://github.com/microsoft/ai-agents-for-beginners.git cd ai-agents-for-beginners git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'CMD (Windows):
git clone --filter=blob:none --sparse https://github.com/microsoft/ai-agents-for-beginners.git cd ai-agents-for-beginners git sparse-checkout set --no-cone "/*" "!translations" "!translated_images"This gives you everything you need to complete the course with a much faster download.
If you wish to have additional translation languages supported, they are listed here.
🌱 Getting Started
This course has 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.
Meet Other Learners, Get Your Questions Answered
If you get stuck or have any questions about building AI Agents, join our dedicated Discord Channel in the Microsoft Foundry Discord.
What You Need
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 examples in these exercises utilize Microsoft Agent Framework with Microsoft Foundry Agent Service V2:
- Microsoft Foundry - Azure Account Required
This course uses the following AI Agent frameworks and services from Microsoft:
Some code samples also support alternative OpenAI-compatible providers such as MiniMax, which offers large-context models (up to 204K tokens). See the Course Setup for configuration details.
For more information on running the code for this course, go to the Course Setup.
🙏 Want to help?
Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request
📂 Each lesson includes
- A written lesson located in the README and a short video
- Python code samples using Microsoft Agent Framework with Microsoft Foundry
- Links to extra resources to continue your learning
🗃️ Lessons
| 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 |
| Using Agentic Protocols (MCP, A2A and NLWeb) | Link | Video | Link |
| Context Engineering for AI Agents | Link | Video | Link |
| Managing Agentic Memory | Link | Video | |
| Exploring Microsoft Agent Framework | Link | ||
| Building Computer Use Agents (CUA) | Link | Link | |
| Deploying Scalable Agents | Link | Link | |
| Creating Local AI Agents | Link | Link | |
| Securing AI Agents | Link | Link |
🎒 Other Courses
Our team produces other courses! Check out:
LangChain
Azure / Edge / MCP / Agents
Generative AI Series
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Core Learning
Copilot Series
🌟 Community Thanks
Thanks to Shivam Goyal for contributing important code samples demonstrating Agentic RAG.
Contributing
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.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
Trademarks
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos is subject to those third-parties' policies.
Getting Help
If you get stuck or have any questions about building AI apps, join:
If you have product feedback or errors while building visit:
