Building Agent using AutoGen

  • IntermediateLevel

  • 9565+Students Enrolled

  • 3 Hrs Duration

  • 4.5Average Rating

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About this Course

  • Learn how to build an agentic AI agent using AutoGen through guided examples and practical workflows.
  • Understand the fundamentals of AutoGen agent creation, role assignment, message handling, and tool integration.
  • Explore how agentic AI improves automation by allowing agents to collaborate, reason, and complete tasks.
  • Work hands on with AutoGen agent frameworks to design multi agent systems with minimal setup.
  • Learn how to deploy an autogen agent for real world tasks such as research, coding, and data extraction.
  • Prepare for autogen certification by learning concepts, best practices, and complete agent implementation.

Learning Outcomes

AutoGen Agent Foundation

Learn to build core AutoGen agents with roles and communication flows.

Agentic AI Skills

Understand how agentic AI improves automation and problem solving

Practical Applications

Build and deploy multi agent workflows using AutoGen in real projects.

Who Should Enroll

  • Beginners interested in building an agentic AI agent using AutoGen for automation and reasoning tasks.
  • Developers who want to learn AutoGen agent creation for multi agent workflows.
  • Professionals exploring agentic AI for intelligent automation and productivity.
  • Learners preparing for autogen certification to validate practical agent building skills.

Course Curriculum

This course teaches how to build an agentic AI agent using AutoGen. Learn AutoGen agent roles, messaging, reasoning cycles, and deployment processes. Build your own autogen agent and understand how agentic AI enables scalable multi agent systems.

toolstools

  1. 1. What is Autogen?

  2. 2. AutoGen: Setting Environment & Installation

  1. 1. AutoGen: Architecture & Working

  2. 2. Build Your First Agent with AutoGen

  3. 3. How Agents work internally?

  4. 4. Agent in AutoChat

  5. 5. MultiModel Input & Structured Output

  6. 6. Teams in Autogen

  7. 7. Project Overview: Build DSA Solver with Agent Team

  8. 8. How can we use different model in the agent?

Meet the instructor

Our instructor and mentors carry years of experience in data industry

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Mayank Aggarwal

Co-Founder Evolvue AI

Educator & Co-Founder passionate about simplifying AI. Formerly at Goldman Sachs & Mindtickle. Creating real-world AI systems with Microsoft AutoGen, empowering learners through YouTube, Udemy & beyond.

Get this Course Now

With this course you’ll get

  • 3 Hours

    Duration

  • Mayank Aggarwal

    Instructor

  • Intermediate

    Level

Certificate of completion

Earn a professional certificate upon course completion

  • Globally recognized certificate
  • Verifiable online credential
  • Enhances professional credibility
certificate

Frequently Asked Questions

Looking for answers to other questions?

An agentic AI agent using AutoGen is an intelligent software agent capable of reasoning, communicating, and performing tasks autonomously. AutoGen provides a structured framework that allows multiple agents to collaborate, use tools, and solve complex problems. This course helps you understand how these agents function and how to build one step by step.

AutoGen simplifies agent building by offering predefined roles, message protocols, tool use, and coordination mechanisms. Developers can create agents that research, plan, analyze, write, or collaborate with other agents. It removes the complexity of manual orchestration and focuses on practical automation.

Basic Python knowledge is helpful, but not mandatory. The course explains each step clearly and provides examples to help beginners build functional agents. Even learners new to agentic AI will be able to understand the concepts and follow the assignments easily.

AutoGen agents can automate research, write summaries, generate content, execute workflows, debug code, search information, or coordinate between multiple tools. They are used in productivity applications, enterprise automation, research pipelines, and AI powered assistants.

Yes. The course covers essential concepts required for autogen certification such as agent roles, workflows, messaging, and practical implementation. It prepares learners with both theory and hands on examples needed to pass certification assessments.

Regular automation follows predefined steps. Agentic AI agents can reason, make decisions, and adjust their actions based on context. With AutoGen, agents can communicate, debate, refine outputs, and collaborate to achieve complex tasks that traditional automation cannot handle.

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