This course provides a practical, framework-agnostic introduction to building advanced multi-agent AI systems. You’ll learn how agentic design patterns and orchestration techniques create modular, maintainable, and intelligent systems capable of solving complex tasks. Through guided instruction and hands-on labs, you’ll explore four major frameworks—LangGraph, CrewAI, BeeAI, and AG2—and understand their strengths, differences, and design philosophies.
You’ll start by using LangGraph to implement foundational workflow patterns, including sequential agents, conditional routing, memory-aware flows, and parallel branches. These patterns serve as building blocks for more complex, adaptive agent systems.
You’ll apply agent orchestration in CrewAI, creating multi-agent workflows using agents, tasks, tools, and structured output schemas. You’ll extend applications with custom tool integrations and learn how CrewAI handles coordination and governance in multi-agent scenarios.
You will also explore BeeAI’s workflow-oriented architecture and AG2’s multi-agent conversation engine, building applications that rely on structured messaging, role-based collaboration, and coordinated problem solving.
By completing the course, you’ll gain the skills to architect flexible, efficient, and production-ready agentic systems, choosing the right framework and workflow patterns for each application.
