AI and Machine Learning
A free 10-lesson course from Microsoft Developer that takes you from the basics of AI agents to building and deploying them, with practical code samples.
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Now playing: What Is agentic RAG?
This learning path is based on the 'AI Agents for Beginners' playlist by Microsoft Developer. It covers what AI agents are, how to choose a framework, design principles, agentic RAG, tool use, planning, memory, multi-agent systems, context engineering, protocols like MCP and A2A, and deployment. Each lesson is a short video, and the full course video includes all lessons in one place. You'll also find links to code samples and a Discord community for questions.
Beginners who want a structured free introduction before deeper practice.
Lesson 1: Full Course (Lessons 1-10) AI Agents for Beginners
This is the full course video combining all 10 lessons. It starts with an introduction to AI agents, then covers choosing a framework, designing good agents, and more. Use this as an overview or to review the entire course in one sitting.
Open on YouTubeLesson 2: What are AI agents?
This lesson defines AI agents and discusses their best use cases. It also covers what you need to start building them, giving you a solid foundation before diving into code.
Open on YouTubeLesson 3: Which AI agent framework to use
Here you learn about agentic frameworks: what they are, why we use them, and how to choose one. The lesson breaks down the parts of an AI agent and explains how frameworks help manage complexity.
Open on YouTubeLesson 4: How to design good AI agents
This lesson focuses on what makes a good AI agent. It covers design principles to follow and examples to guide your own agent design, helping you build agents that are reliable and effective.
Open on YouTubeLesson 5: What Is agentic RAG?
You'll learn what agentic RAG is and how it differs from basic RAG. The lesson explains how to use agentic RAG in applications to improve information retrieval and decision-making.
Open on YouTubeLesson 6: What Is the Agent Tool Use Design Pattern?
This lesson covers the tool use design pattern for AI agents. You'll see how it helps agents do more by using external tools, and what you should plan for when implementing it.
Open on YouTubeLesson 7: What Is the AI Agent Planning Design Pattern?
In lesson 7, you'll explore the planning design pattern. It shows how agents can break down complex tasks into steps, and how you can use this pattern in your own agents.
Open on YouTubeLesson 8: How to use a multi-AI agent system
This lesson explains the multi-AI agent design pattern. You'll learn when to use multiple agents instead of one, and what controls developers have over them.
Open on YouTubeLesson 9: Using Agentic Protocols (MCP, A2A, and NLWeb)
Here you'll learn about three agentic protocols: Model Context Protocol (MCP), A2A, and NLWeb. The lesson explains what they are and how they enable agent interoperability.
Open on YouTubeLesson 10: AI Agent Memory: Building Self-Improving Agents
This lesson focuses on memory management for AI agents. You'll learn how memory enables self-improvement and personalization, and how to build these features into your agents.
Open on YouTubeLesson 11: How can AI agents improve?
This lesson discusses metacognition in AI agents: how agents can improve over time by reflecting on their own performance. You'll learn how to leverage this for better agent outcomes.
Open on YouTubeLesson 12: Building Computer Use Agents (CUA)
This lesson covers computer use agents (CUA): what they are, how they work, different types, and security concerns. It's a practical look at agents that interact with computer interfaces.
Open on YouTubeLesson 13: How to deploy AI agents into production
In this final lesson, you'll learn how to deploy AI agents to production effectively. It covers common mistakes and ways to manage costs, ensuring your agents run smoothly at scale.
Open on YouTubeLesson 14: Context engineering for AI agents
Open on YouTubeLesson 15: How to build effective AI agents
Open on YouTube0 of 15 lessons completed (0%).
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