ai agents for beginners

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Basic Information

This repository is a free, open course designed to teach beginners the fundamentals of building AI agents. It contains 11 lessons that each focus on a specific topic in agent design and engineering, such as agentic frameworks, design patterns, tool use, retrieval-augmented generation, planning, multi-agent systems, metacognition, trustworthiness, production, and the Model Context Protocol. Each lesson provides a written README, a short video, and runnable Python code examples that integrate with Azure AI Foundry and GitHub Model catalogs. The materials reference Microsoft agent frameworks including Azure AI Agent Service, Semantic Kernel, and AutoGen. The repo includes a code_samples folder and a Course Setup guide to help learners run the examples. The content is maintained with multi-language translations and community contributions to make agent concepts accessible globally.

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Features
Structured curriculum of 11 lessons covering core agent topics and advanced patterns. Each lesson includes written explanations, a short video, and Python code examples targeted at Azure AI Foundry and GitHub Models. Demonstrations and samples show patterns such as tool use, agentic RAG, planning, multi-agent design, metacognition, and production readiness. The course links to additional learning resources and related beginner courses. Repository supports automated multi-language translations via a GitHub Action so content is kept up to date in many languages. Code samples are organized for hands-on learning and the project encourages contributions under Microsoft’s CLA and code of conduct. Community support channels such as a Discord and developer forum are highlighted for questions and feedback.
Use Cases
The course helps newcomers rapidly understand both conceptual and practical aspects of building AI agents by combining lessons, videos, and runnable code. Learners can follow step-by-step examples that use real model catalogs and Azure services, enabling them to experiment with agent design patterns and deployable practices. The variety of topics — from foundational agent use cases to multi-agent systems and production considerations — equips learners to choose appropriate patterns for their problems. Multi-language support and community channels lower barriers for non-English speakers and provide ways to get help. Links to related beginner courses let learners extend skills into model context protocols, generative AI, and broader machine learning topics. Forking the repo and running the Course Setup enables immediate hands-on practice.

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