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AI Agents for Beginners: From Concept to Code

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.

Learn from: the original creator. Original content published on YouTube. DigitalSkillX organizes these public resources into a structured learning path. DigitalSkillX does not claim ownership or partnership.

Lessons
15
Time
About 3 hr 11 min
Level
beginner

Now playing: What Is agentic RAG?

About this path

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.

What you will learn

  • Understand what AI agents are and their best use cases.
  • Learn how to choose the right agent framework for your project.
  • Apply design principles to create effective AI agents.
  • Implement agentic RAG and tool use patterns.
  • Use planning, memory, and multi-agent systems to enhance agent capabilities.
  • Manage context and use protocols like MCP and A2A.
  • Deploy AI agents to production with security and cost considerations.

Who this is for

Beginners who want a structured free introduction before deeper practice.

Curriculum

Section 1: Foundations of AI Agents

  1. 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 YouTube
  2. Lesson 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 YouTube
  3. Lesson 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 YouTube
  4. Lesson 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 YouTube

Section 2: Core Design Patterns

  1. Lesson 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 YouTube
  2. Lesson 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 YouTube
  3. Lesson 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 YouTube

Section 3: Advanced Topics and Deployment

  1. Lesson 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 YouTube
  2. Lesson 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 YouTube
  3. Lesson 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 YouTube
  4. Lesson 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 YouTube
  5. Lesson 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 YouTube
  6. Lesson 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 YouTube

Section 4: Additional lessons

  1. Lesson 14: Context engineering for AI agents

    Open on YouTube
  2. Lesson 15: How to build effective AI agents

    Open on YouTube

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