Learn to build multi-agent AI systems with CrewAI in about 45 minutes. Understand the crew/agent/task model, define specialized agents, create tasks, and build a real-world market research crew with analyst, researcher, and writer agents.
CrewAI is a Python framework for building multi-agent AI systems where specialized agents collaborate on complex tasks. This free intermediate course walks you through the core crew/agent/task model in about 45 minutes, giving you enough hands-on depth to go from zero to a working agent crew. You will learn how to define agents with distinct roles and goals, wire them together with tasks, and assemble them into a crew that runs as a coordinated pipeline.
The course builds toward a real-world market research project. You will construct a three-agent crew made up of a researcher, an analyst, and a writer, each with its own responsibility in the workflow. Along the way you will explore advanced patterns including memory and custom tools, so your agents can retain context and take actions beyond simple text generation.
This course suits developers and technically curious learners who already know basic Python and want to move beyond single-agent chatbots into proper multi-agent orchestration. No prior experience with agent frameworks is required. Finish all lessons and pass the final exam to earn a free certificate of completion you can add to your LinkedIn profile or resume.
1 modules • 6 lessons
Finish every lesson and pass the final exam to earn this free, shareable certificate.
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June 15, 2026
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The course teaches you how to build multi-agent AI systems using the CrewAI Python framework. You will learn the crew, agent, and task model, then apply it by building a real market research pipeline with three collaborating agents.
Yes, the course is completely free. You can also earn a certificate of completion at no cost by finishing the lessons and passing the final exam.
You should be comfortable writing basic Python, including functions and classes. No prior experience with agent frameworks like CrewAI or AutoGen is needed, though familiarity with calling an LLM API is helpful.
The course focuses entirely on CrewAI. Topics include defining agents with roles and goals, creating tasks, assembling a crew, using memory for context retention, adding custom tools, and completing a real-world market research project.
Yes. Completing all lessons and passing the final exam earns you a certificate of completion. You can share it on LinkedIn or include it on your resume to demonstrate your multi-agent AI skills.
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