Description

Building AI Agents & Agentic AI Systems Using AutoGen – Complete Hands-On Course

Requirements

• Basic Python Knowledge – Understanding Python syntax, functions, classes, and OOP concepts.

• API Familiarity – Experience with REST APIs or third-party libraries for integrating LLM tools.

• Introductory AI/ML Basics – Awareness of how large language models work (prompts, tokens, model behavior).

• Command Line Skills – Ability to use terminal/CLI for installing packages and running scripts.

• Python Environment Setup – Knowledge of creating and managing virtual environments (venv/conda) and installing dependencies via pip.

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Course Description

Unlock the future of intelligent software development with “Building AI Agents and Agentic AI Systems Using AutoGen.”
This project-driven course guides you step-by-step into the world of Agentic AI, where multiple AI agents collaborate, plan, and execute tasks autonomously.

Using Microsoft AutoGen, you’ll learn how to create powerful multi-agent systems capable of reasoning, coding, research automation, decision-making, and tool integration. Each module is designed to give you practical, real-world skills you can apply immediately.

This course is perfect for data scientists, machine learning engineers, researchers, developers, and product builders who want to build next-generation AI applications that go far beyond simple chatbots.

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What You Will Learn

Core Agentic AI Concepts

• Fundamentals of Agentic AI and how it differs from standard GenAI workflows

• How AutoGen orchestrates multiple agents for collaborative problem-solving

Building & Customizing Agents

• Creating agents such as UserProxyAgent, AssistantAgent, and GroupChatAgent

• Configuring agent roles, prompts, and communication flows

Developing Multi-Agent Workflows

• Real-world use cases for autonomous coding, research tasks, planning, and data processing

• Task decomposition, reasoning, and multi-step collaboration

Tool & API Integration

• Connecting agents to external tools such as web APIs, databases, and custom Python functions

• Leveraging AutoGen to automate real tasks end-to-end

AutoGen Studio

• Visual workflow building

• Monitoring agent conversations and debugging interactions

Performance Optimization

• Reducing cost and latency with configuration tuning

• Role specialization and workflow optimization

Deployment & Real-World Applications

• Building coding assistants

• Research automation bots

• Multi-agent chat applications

• Automated task runners and workflow engines

You’ll not only learn the theory—you’ll build complete AI agent systems from scratch that mimic real human workflows through collaboration, communication, and intelligent decision-making.

The course also includes a comparison of AutoGen vs LangChain vs CrewAI, helping you choose the best framework for your specific use case.

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Who Should Take This Course?

Perfect for:

• ML & AI Professionals looking to transition into agentic system development

• Developers & Engineers building advanced AI-driven applications

• GenAI Enthusiasts eager to explore multi-agent workflows and automation

• Startup Founders & Product Teams building AI-first products

• Students & Researchers working on NLP, MLOps, or intelligent systems

• Freelancers & Entrepreneurs wanting to create AI-powered tools, automate workflows, or launch AI-based services

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Outcome

By the end of this course, you will have the expertise to:

• Build fully autonomous AI agent teams

• Design collaborative multi-agent workflows

• Integrate LLMs with real-world tools and APIs

• Optimize and deploy production-ready agentic systems

You’ll gain the confidence to create advanced AI ecosystems capable of planning, reasoning, and acting—just like real human teams.

Please Note: Files will be included in this purchase only Full Course Video & Course Resources. You will get cloud storage download link with life time download access.