AI Agents for Beginners

AI Agents for Beginners is Microsoft's open course for developers who want a path from agent concepts to working systems. Its 18 lessons connect design patterns, tool use, agentic RAG, planning, multi-agent orchestration, context engineering, memory, Microsoft Agent Framework, browser use, deployment, local agents, and security. Written guides, short videos, Python notebooks, .NET samples, knowledge checks, and assignments make it useful as both a self-study course and a team curriculum.

Use a shallow clone, create an isolated Python 3.12 environment, copy the example environment file, and begin with the setup lesson. Provision Microsoft Foundry resources only when a selected notebook requires them.

Help me safely set up AI Agents for Beginners from https://github.com/microsoft/ai-agents-for-beginners. First read README.md, 00-course-setup/README.md, .env.example, requirements.txt, SECURITY.md, and LICENSE at commit 25b7985f3b2dc37a84f4a7387ccd3c9f0e5b1595. Confirm Git, Python 3.12+, available disk space, whether I need Python or .NET, and whether I want the Microsoft Foundry cloud path or Foundry Local. Use a shallow or sparse clone because the complete repository history is about 3 GB. Create an isolated virtual environment before installing requirements. Never print, commit, or invent endpoints, subscription identifiers, connection IDs, API keys, or tokens. Ask before Azure login, resource creation, paid model calls, browser control, deployment, or file operations outside the course directory. Start with one low-risk notebook, report every command and file change, and separate documentation claims from observed results.

git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git

1. 1
   Choose a learning path

   New learners should follow Lessons 01 through 06 in order. Developers with a specific goal can use STUDY_GUIDE.md to select paths for tools, RAG, multi-agent systems, production, or local agents.

2. 2
   Clone only what you need

   Use a depth-one clone for the complete current course, or sparse checkout for the setup lesson and selected lesson directories. This avoids downloading roughly 3 GB of translation assets and history.

3. 3
   Prepare an isolated runtime

   Create a Python 3.12 virtual environment and install requirements.txt. Install .NET 10 only when following .NET samples.

4. 4
   Configure one provider path

   For the primary path, authenticate with Azure CLI and set the documented Microsoft Foundry endpoint and model deployment in a local .env file. Configure optional services only for the lessons that use them.

5. 5
   Run a low-risk lesson

   Begin with an early notebook that does not deploy infrastructure or control a browser. Review outputs, token usage, data sent to the provider, and any created files.

6. 6
   Add production checks gradually

   When moving toward deployment, use the course material on trust, evaluation, observability, smoke tests, and security. Treat the educational examples as starting points that still need project-specific review.

AI Agents for Beginners earns its place as a substantial learning resource because the curriculum connects core concepts to maintained code, assignments, testing material, deployment guidance, and security topics. The study guide makes the breadth navigable, and the changelog shows recent migration work around Microsoft Agent Framework and Foundry. The main cost is operational. Most runnable cloud examples need Azure resources, some lessons add specialized services, and the unversioned repository requires commit-level review for repeatable training. Public documentation and source were checked for this entry; AgentMatter did not independently execute the notebooks.