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Udemy

Learn Agentic AI – Build Multi-Agent Automation Workflows

via Udemy

Overview

Build Autonomous AI Agents with AutoGen & MCP –End-to-End Agentic AI Workflows with 6 Agents for Real-World Automation

What you'll learn:
  • Get a detailed understanding of LLMs, AI Agents, MCP, Multi-Agent Systems, and Agentic AI
  • Build Multi Agentic workflows using Microsoft AutoGen Framework
  • Develop Specialized Agents such as Jira Agent for Bug analysis, Playwright Agent for browser Automation, API Agent for testing, DB Agent for data analysis
  • Build intelligent, autonomous AI agents that collaborate, self-correct, and execute complex tasks without constant human intervention
  • Understand the power of Context Engineering to enable AI agents to work effectively toward defined goals
  • Gain a thorough understanding of AutoGen framework concepts including Assistant Agents, human-in-the-loop collaboration, termination strategies, and state-savin
  • Build an Agent Factory design pattern to create reusable specialized agents for multi-purpose use
  • Get in-depth knowledge of MCPs and how their configurations are defined for real-world applications

Welcome to the future of AI automation – Agentic AI with the AutoGen Framework. This course is your ultimate guide to building intelligent, autonomous AI agents that collaborate, self-correct, and execute complex tasks without constant human intervention.
Even if you're new to this space, we start from the absolute basics—no prior knowledge of agent frameworks is required.

You’ll start by mastering the core foundations – Large Language Models (LLMs), AI Agents, Multi-Agents, and the Model Context Protocol (MCP), which serves as the backbone for agent-to-tool communication. Next, you’ll learn how to engineer contexts and craft prompts that unlock the true potential of your AI agents.

Through hands-on projects, you’ll build real-world agents like Browser Automation Agents, Database Agents, API Agents, and Jira Agents. We’ll go beyond theory with advanced collaboration patterns, including multi-agent group chats, context-driven workflows, and automated validation.

By the end, you’ll have the skills to create production-ready agentic systems using the Agent Factory Pattern, empowering you to design reusable, scalable, and highly efficient AI workflows.

If you’re ready to level up from AI users to AI builders, this course will give you the tools and mindset to lead the next wave of AI innovation.

This course uses Python Stack & Python basics has been thoroughly discussed in the last section of the course for brush up.

Syllabus

  • Essentials of LLMs, AI Agents & MCP Servers – Build Conceptual Clarity
  • Getting Deep Diver into MCP Server to build an AI Agent with claude
  • Intro to Agentic AI & Setup Python IDE environment for AutoGen Framework
  • AutoGen Framework fundamentals - AssitantAgents, RoundRobinGroupchat Concepts
  • AutoGen Framework fundamentals - Termination, StateSaving, HumanInLoop concepts
  • AutoGen Framework fundamentals - SelectorGroupChat, mcpworkbench & BrowserAgent
  • Understand the Goal of the Agentic workflow & setup Agents Prerequisites -Jira
  • Use Jira Agent & Playwright Agent to Build Autonomous Multi Agentic Workflow
  • Agent Factory Pattern-Design Multi Agent system with Database, API, Excel Agents
  • Context Engineering - Define System messages to Agents for internal coordination
  • Summary - Recap - what did we learn? How this skill help in my next career leap?
  • Glossary - Learn Python Fundamentals
  • Bonus Lecture

Taught by

Rahul Shetty Academy

Reviews

4.6 rating at Udemy based on 1610 ratings

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