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Agentic AI: LangGraph, CrewAI, AutoGen, and BeeAI

PremiumIntermediateCourse

Build multi-agent AI systems using LangGraph, CrewAI, BeeAI, and AG2 by mastering agentic design patterns, orchestration workflows, and collaborative agent behaviors for scalable AI applications.

Language

  • English

Topic

  • Artificial Intelligence

Industries

  • Information Technology

Skills You Will Learn

  • Agentic AI, Autogen, BeeAI, Generative AI, LangChain, LangGraph

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 12 Hours

Platform

  • SkillsNetwork

Last Update

  • February 19, 2026
About this Course
Learn how to develop intelligent, autonomous multi-agent systems using today’s leading agentic AI frameworks. This course teaches you how to apply agentic design principles, workflow patterns, and orchestration strategies to build scalable AI systems that plan, reason, and collaborate. You’ll explore foundational concepts behind agentic architectures and learn how to choose the right framework based on use case, complexity, and required system behaviors.

After completing this course, you will be able to:

  • Design optimized AI systems by selecting and combining appropriate agentic frameworks and architectural patterns
  • Implement AI workflow patterns using agentic design principles and LangGraph
  • Build structured multi-agent workflows using CrewAI, including agents, tasks, and custom tools
  • Develop AI applications with BeeAI and design conversation-driven interactions using AG2
  • Combine orchestration strategies with modular workflows to create scalable multi-agent systems
  • Evaluate the strengths and use cases of LangGraph, CrewAI, BeeAI, and AG2 to choose the best tool for a given application

You’ll begin with LangGraph, implementing workflow patterns such as sequential execution, routing, conditional flows, and parallelization. Hands-on labs teach you how to use these patterns to structure dynamic agent interactions and maintain clean, maintainable system designs.

You’ll learn CrewAI, working with agents, tasks, and crews to build structured multi-agent applications. You’ll generate structured outputs with YAML and Pydantic, integrate custom tools, and orchestrate collaborative operations across multiple agents.

The course then introduces BeeAI and AG2, where you’ll build agents that manage workflows, coordinate reasoning steps, and engage in role-based conversations. You’ll design multi-agent dialogues, extend capabilities with plugins, and implement applied use cases such as healthcare assistants or enterprise automations.

By the end of the course, you’ll have hands-on experience building multi-agent workflows across multiple frameworks and selecting the right patterns to optimize real-world AI systems.

The following skills are required to be successful with this course: 
 
  • Working knowledge of Python programming, LangChain, and LangGraph, along with an understanding of how agentic AI systems work.


Course Syllabus


Welcome

  • Course Introduction
  • Course Overview
  • RAG and Agentic AI Professional Certificate Overview
  • Helpful Tips for Course Completion


Module 1: Agentic Frameworks and LangGraph Design Patterns for Effective AI Systems

  • Module Summary and Learning Objectives
  • Introduction to Agentic Frameworks
  • Understanding Agentic AI and Open Source Frameworks
  • Building AI Agents with Open Source Frameworks
  • Practice Quiz: Introduction to Agentic Frameworks
  • Understand AI System Design Patterns
  • Essential Design Patterns for AI Systems
  • Orchestrator Design Pattern
  • Evaluator-Optimizer Design Pattern
  • Lab: Implement Workflow Patterns with LangGraph
  • Practice Quiz: Understand AI System Design Patterns
  • Cheat Sheet: Agentic Frameworks and Design Patterns for Effective AI Systems
  • Graded Quiz: Agentic Frameworks and Design Patterns for Effective AI Systems


Module 2: CrewAI Fundamentals and Advanced Applications

  • Module Summary and Learning Objectives
  • Introduction to CrewAI
  • Design AI Agent Workflows with CrewAI
  • Lab: CrewAI 101: Building Multi-Agent AI Systems
  • Practice Quiz: Introduction to CrewAI
  • Structured Outputs in CrewAI
  • CrewAI with Structured Outputs, YAML, and CrewBase
  • Lab: Create a Structured Meal & Grocery Planner with CrewAI
  • Reading: Structured Outputs in CrewAI
  • Practice Quiz: Structured Outputs in CrewAI
  • Functions and CrewAI
  • Extending CrewAI with Custom Functions
  • Lab: Agents with Tools vs. Tasks with Tools in CrewAI
  • Practice Quiz: Functions and CrewAI
  • Lab: Building Your Own AI Nutrition Coach Using a Multi-Agent System
  • Summary and Highlights
  • Cheat Sheet: CrewAI Fundamentals and Advanced Applications
  • Graded Quiz: CrewAI Fundamentals and Advanced Applications


Module 3: Alternative Agentic Frameworks: BeeAI and AG2 (AutoGen)

  • Module Summary and Learning Objectives
  • BeeAI Core Concepts and Architecture
  • BeeAI: Introduction and Core Components
  • Building Agents with the BeeAI Framework
  • Lab: Building Agentic AI Systems with the BeeAI Framework
  • Practice Quiz: BeeAI Core Concepts and Architecture
  • AG2 (AutoGen) Core Concepts, Architecture, and Conversations
  • Introduction to AG2 (AutoGen) and Its Key Elements
  • Extending AG2 with Tools and Structured Outputs
  • Reading: Agent Orchestration and Design Patterns in AG2
  • Lab: AG2 101 (AutoGen): Complete Tutorial
  • Lab: Build Multi-Agent Chatbot with AG2 (AutoGen)