Skills you will learn

  • Core concepts behind AutoGen and how it operates
  • Setting up and running AutoGen agents from scratch
  • Customizing agent behavior for specific roles and tasks
  • Designing systems where multiple agents work as a team
  • Applying AutoGen to practical automation scenarios
  • Understanding how agents communicate and hand off tasks

Who should learn

  • Beginners
  • Software Developers
  • AI Engineers
  • Data Scientists
  • DevOps Engineers
  • Product Managers
  • Students

What you will learn

  • Learn to Build AI Agents with AutoGen

    • Lesson 01: Introduction

      • 1.01 Course Introduction
        02:13
    • Lesson 02: Introduction to AutoGen

      • 2.01 AutoGen and Multi Agent Framework
        03:38
      • 2.02 AutoGen Agent Types
        03:26
      • 2.03 Demo: Build Your First AutoGen Agents Using Azure API
        10:17
    • Lesson 03: Advanced Agent Configurations ​

      • 3.01 Advanced Agent Configurations
        02:44
      • 3.02 Memory and Context Awareness
        02:20
      • 3.03 Demo: IT Helpdesk Chatbot: Enabling Memory and Context Awareness
        12:48
      • 3.04 Multi Step Reasoning
        02:37
      • 3.05 Demo: Configure Multi-Step Reasoning in AutoGen for AI-Powered Troubleshooting
        12:21
      • 3.06 Customizing Agents with LLMs
        02:52
      • 3.07 Demo: Agent Behavior Customization in AutoGen for IT Support
        11:03
    • Lesson 04: AutoGen Agent Collaboration

      • 4.01 Agent-to-Agent Communication
        02:23
      • 4.02 Demo: AutoGen Agent Collaboration for Smarter Troubleshooting
        09:13
      • 4.03 Task Delegation and Decision Making
        02:55
      • 4.04 Demo: AI-Driven Task Delegation in IT Support
        11:24
      • 4.05 Multi-Agent Workflows
        03:03
      • 4.06 Demo: AI-Powered IT Support with Multi-Agent Interaction
        12:42
      • 4.07 Demo: Implementation of AutoGen in LangGraph Workflows
        09:49
      • 4.08 Demo: AutoGen Weather Assistant
        06:41
      • 4.09 Demo: AutoGen for Automated Contract Review and Compliance Check
        10:31
    • Lesson 05: Key Takeways

      • 5.01 Key Takeaways
        01:59
About the Course

AutoGen is changing the way developers use AI. Instead of relying on a single model for every job, AutoGen lets you create teams of smart agents that talk to each other, share tasks, and work as a group. In this course, you will find out what AutoGen is, how it works, and how to set up agents for different goals. You will start with the basics and gradually learn how to build multi-agent systems that work well together. If you want to create real AI agent workflows but do not know where to begin, this course will give you clear and practical steps.

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FAQs

  • Is this course free?

    Yes, the entire course is available at no cost and you will still receive a professional certificate once you finish all the lessons.

  • I have no experience with AI agents. Is that okay?

    That is completely fine. The course was put together with first-timers in mind. Everything is explained from the ground up so you are never left guessing or expected to already know something that has not been covered yet.

  • Do I need coding experience to take this course?

    Python experience will help, but the course is designed to be easy to follow even if you do not have much programming experience.

  • What exactly is Auto Gen?

    AutoGen is an open-source framework from Microsoft Research that makes it straightforward to build systems where multiple AI agents work together. Each agent can have its own role, and they communicate with each other to complete tasks that would be too complex for a single model to handle on its own.

  • How is AutoGen different from using a regular AI chatbot?

    A regular chatbot is a single model responding to a single user. AutoGen lets you create entire teams of agents, each with different responsibilities, that coordinate and collaborate automatically to get work done without constant human input.

  • What will I be able to build after finishing this course?

    You will have a strong foundation to start creating multi-agent workflows. Different agents will take on specific roles, communicate, and work together to complete tasks using AutoGen. You will also learn how to adjust agent behavior and roles for more advanced and specific use cases.

  • How does agent collaboration actually work in AutoGen?

    In AutoGen, agents are set up to send and receive messages from each other. Based on those messages they decide what action to take next, which creates a natural back-and-forth that mimics how a team of people might divide and tackle a problem together.

  • Is there a time limit on completing the course?

    No, the course is fully self-paced so you can take as long as you need and revisit any lesson whenever it is convenient for you.

  • Will this certificate help me get a job?

    Yes, it adds credibility, especially for jobs in AI automation and agent development. When you combine it with your own GitHub projects, it gives hiring managers clear proof of your skills.

  • Can I do this course on my phone?

    Yes, the course works on mobile devices so you can learn during your commute, lunch break, or whenever you have a few free minutes.

  • Does this course go into advanced configurations?

    Yes, Lesson 03 is dedicated entirely to advanced agent configurations, walking you through how to tailor agent behavior and roles to fit more specific and demanding use cases beyond the basics

  • How does AutoGen compare to CrewAI or LangGraph?

    All three handle multi-agent workflows but in different ways. AutoGen leans into conversational agent interactions, CrewAI is built around role-based agent teams, and LangGraph uses a graph-based approach for stateful workflows. Learning AutoGen gives you a strong foundation and a unique perspective that complements the other frameworks nicely.

  • Is the content up to date?

    Yes, the course reflects the current state of AutoGen and multi-agent AI development, giving you knowledge that is relevant to what the industry is actually using and building with right now.

  • What should I explore after finishing this course?

    Consider diving into LangGraph or CrewAI to see how other multi-agent frameworks approach similar problems, and experiment with retrieval augmented generation and agent memory to take your AutoGen projects to the next level.

  • Can I add this to my LinkedIn profile?

    Absolutely. Once you earn your certificate you can list it under Licenses and Certifications on LinkedIn, which helps your profile stand out to recruiters looking for AI and automation skills.

  • Acknowledgement
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, OPM3 and the PMI ATP seal are the registered marks of the Project Management Institute, Inc.
  • *All trademarks are the property of their respective owners and their inclusion does not imply endorsement or affiliation.
  • Career Impact Results vary based on experience and numerous factors.