Building Agent using AutoGen

Artificial Intelligence is evolving beyond traditional chatbots into intelligent, autonomous agents capable of reasoning, collaborating, and solving complex problems with minimal human intervention. Building Agents using AutoGen is a comprehensive course designed to introduce learners to Microsoft AutoGen, one of the leading frameworks for developing AI-powered multi-agent systems. Whether you’re an AI enthusiast, software developer, or machine learning practitioner, this course provides the knowledge and practical skills needed to build intelligent agent-based applications using modern Large Language Models (LLMs).

The course begins by introducing the fundamentals of AutoGen and guiding learners through the complete environment setup and installation process. Students will configure the required development tools, install the AutoGen framework, and prepare their systems for building and testing AI agents. This foundation ensures learners are ready to develop scalable agent-based applications throughout the course.

As learners progress, they will explore the architecture of AutoGen and understand how intelligent agents communicate, reason, and execute tasks using Large Language Models. The course demonstrates how to build a first AI agent from scratch while explaining the internal working of agents, including message passing, reasoning, memory management, and conversation handling. Students will gain a deeper understanding of how autonomous agents make decisions and collaborate to solve complex problems.

The course also explores advanced AutoGen capabilities, including AutoChat, multi-model support, multimodal inputs, and structured outputs. Learners will discover how to integrate different language models into a single application, process text and image-based inputs, and generate structured responses suitable for enterprise applications. These concepts enable developers to build more flexible, intelligent, and production-ready AI systems.

A key focus of the course is multi-agent collaboration, where learners will create specialized AI agent teams capable of working together to accomplish shared objectives. They will understand how tasks can be distributed among multiple agents, how collaborative decision-making improves problem-solving, and how agent teams can automate sophisticated workflows that would be difficult for a single AI model to handle.

The course concludes with a practical capstone project in which learners build a Data Structures and Algorithms (DSA) Solver using an AutoGen agent team. This real-world project combines all the concepts covered throughout the course, demonstrating how multiple AI agents can collaborate to analyze programming problems, generate optimized solutions, validate outputs, and provide structured explanations. By the end of the course, learners will have the confidence to design, develop, and deploy intelligent multi-agent AI applications using the AutoGen framework.

What You’ll Learn

• Understand the fundamentals of Microsoft’s AutoGen framework.
• Install and configure AutoGen for AI agent development.
• Learn the architecture and workflow of intelligent AI agents.
• Build your first AI agent using AutoGen.
• Understand how AI agents communicate, reason, and make decisions.
• Explore AutoChat and multi-agent conversations.
• Integrate multiple Large Language Models (LLMs) into AutoGen applications.
• Work with multimodal inputs, including text and images.
• Generate structured outputs such as JSON and formatted responses.
• Build and manage collaborative AI agent teams.
• Design scalable multi-agent workflows for real-world applications.
• Develop a practical DSA Solver project using multiple AI agents.
• Apply AutoGen concepts to automate complex tasks and intelligent workflows.
• Build a strong foundation for creating next-generation autonomous AI systems.

Target Audience

• AI Engineers
• Machine Learning Engineers
• Python Developers
• Software Developers
• Generative AI Developers
• LLM Application Developers
• Data Scientists
• Automation Engineers
• Computer Science Students
• Anyone interested in building intelligent AI agents and multi-agent systems

Prerequisites

• Basic knowledge of Python programming.
• Familiarity with Artificial Intelligence or Machine Learning concepts is helpful but not required.
• Basic understanding of Large Language Models (LLMs) is beneficial.
• A computer with Python installed and internet access for installing AutoGen and required dependencies.
• Enthusiasm to learn modern AI agent development through hands-on examples and real-world projects.