Design, Develop, and Deploy Multi-Agent Systems with CrewAI

Multi-agent systems let generative AI go beyond single tasks, enabling teams of agents that can plan, reason, and collaborate to solve complex problems. In this course, you’ll learn how to build multi-agent systems that automate complex, end-to-end workflows. You’ll create intelligent agent teams that plan, reason, and collaborate using tools, memory, and guardrails, and learn how to scale them for production. Across four modules, you’ll build practical applications including an automated code reviewer, a meeting co-pilot, and a deep researcher, each showcasing real-world design patterns for agent collaboration. You’ll monitor and debug agent performance using traces, evaluate behavior with LLM-as-a-Judge, and apply best practices for continuous improvement in production. By the end, you’ll be able to implement custom multi-agent systems that perform reliably, deliver measurable outcomes, and scale to thousands of users

• Build practical multi-agent systems that collaborate, use tools and memory, and scale reliably to production
• Use tools such as web search and MCP servers to extend your agents’ real-world capabilities
• Add guardrails, hooks, and low level control with CrewAI Flows to make AI systems safer, more predictable, and production-ready

• Basic computer and internet skills are helpful
• Ability to read course instructions in English and complete short practice activities