AI Agents for Beginners
A free 18-lesson course that teaches you everything you need to start building AI Agents.
The evidence shows this is an educational course repository, not a deployable Agent product. There is no implementation of least privilege, user confirmation, data flow transparency, sensitive data handling, dependency security, external effects, rollback, or source attribution. All trust criteria score 0 because there is no evidence these mechanisms exist.
Self-consistency: The course structure is clear, and lesson READMEs and code samples correspond without contradictions. Dependency availability: requirements.txt lists dependencies with pinned versions, but no lock file is provided, so availability is moderate. Failure messages: Code samples may include error handling, but it is not explicitly shown in the provided files, so score is low.
Audience and scenarios: Clearly targets beginners with 18 lessons covering various scenarios. Capability boundaries: The course describes the frameworks and services used, but does not define Agent capability boundaries. Trigger precision: As a course, there is no explicit trigger mechanism. Environment fit: Multi-language support and local clone guidance are provided, but detailed environment configuration is not fully covered.
Information architecture: README provides a clear course outline and navigation. Install notes: Clone and sparse checkout instructions are provided, but detailed installation steps are missing. Naming stability: Course names and directory structure are stable. Examples and FAQ: Extensive code examples and extra learning resources are provided, but no FAQ. Known limitations: Not explicitly listed. License: MIT license is clear. Versioning/changelog: Not provided. Maintenance responsibility: Maintained by Microsoft with contribution guidelines.
Output usability: Course content is directly usable for learning, and code samples are runnable. Marginal value: As an educational course, it provides a systematic learning path with high value. Cost-benefit: Free and open source, low cost, high benefit.
Claim traceability: Claims in the course are mostly supported by links. Cross-source corroboration: Some content has external links, but no independent verification. Fact-inference separation: Course content distinguishes facts and teaching suggestions, but not explicitly labeled.
- This repository is an educational course, not a deployable Agent product, so trust-related criteria are not applicable.
- Dependencies are pinned but no lock file is provided, posing potential dependency availability risks.
- Known limitations and changelog are not provided; users need to assess on their own.
What does this agent do, and when should you use it?
Microsoft's AI Agents for Beginners is a comprehensive, free course designed to teach the fundamentals of building AI agents. It consists of 18 lessons covering topics such as intro to AI agents, exploring agentic frameworks, design patterns (tool use, agentic RAG, planning, multi-agent, metacognition), production deployment, protocols (MCP, A2A), context engineering, memory management, and security. Each lesson includes a written tutorial, a short video, and Python code samples using Microsoft Agent Framework with Microsoft Foundry Agent Service V2. The repository supports 50+ language translations and includes a Discord community for learners to get help.
This repository provides educational content in the form of 18 markdown lessons, each with a README tutorial and Python code in the code_samples folder. The code demonstrates building agents with Microsoft Agent Framework and Microsoft Foundry Agent Service V2, covering patterns like agentic RAG, multi-agent collaboration, tool use, and more. Users configure Azure and Foundry services, run the code, and learn from practical examples. The repo also includes video links, extra learning resources, and automated multi-language translations via GitHub Actions.
- Beginners who want a structured, comprehensive path to learn AI agent development from scratch.
- Developers seeking to understand Microsoft Agent Framework and Foundry for building production agents.
- Educators looking for ready-made, multi-language course material for teaching AI concepts.
- Developers needing concrete code examples for agentic RAG, multi-agent patterns, etc., to reference in their own projects.
- Community learners who want to engage with others via Discord to ask questions and share progress.
What are this agent's strengths and limitations?
- Structured curriculum covering 18 topics from intro to advanced, suitable for self-paced learning.
- Practical Python code examples using Microsoft's own agent framework, giving hands-on experience.
- Extensive multi-language support (50+) automatically updated, making it accessible globally.
- Includes videos and links to extra learning resources, enhancing the learning experience.
- Code samples are tied to Microsoft Agent Framework and Foundry, requiring an Azure account—potential vendor lock-in.
- The course is heavily Microsoft-centric; developers preferring other frameworks may find it less relevant.
- It is a tutorial only, not a deployable application; you must build your own agents based on what you learn.
- Some advanced lessons (e.g., browser automation) may require additional setup or dependencies.
How do you install or deploy this agent?
No installation needed; you can access the course content directly on GitHub. To clone the repository without translations (for a lighter download), use: git clone --filter=blob:none --sparse https://github.com/microsoft/ai-agents-for-beginners.git, then cd into the folder and run git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'.
How do you use this agent?
- Navigate to a lesson folder (e.g., 01-intro-to-ai-agents) and read the README tutorial, watch the video. 2. Set up an Azure account and Microsoft Foundry service as required. 3. Run the Python code in the code_samples folder, ensuring you have Python installed and dependencies configured. 4. Fork the repository to experiment and modify the code.