CrewAI gives you a structure for getting multiple AI agents to work together on a task instead of one model doing everything alone, and this Zero To Mastery course teaches that structure hands-on.
What you'll learn
- Designing agent roles such as Supervisor, Researcher, and Action Executor
- Using an LLM for decision-making and task-specific execution
- Building tool-based actions for data retrieval and API calls
- Connecting multiple agents so they collaborate dynamically
- Configuring prompts to shape agent behavior and output
Across 26 lessons, you move from simple single-agent workflows up to a full multi-agent system, finishing with a working AI interview coach built entirely on CrewAI — a practical target if you want agents that actually complete tasks rather than just converse.
What you will learn:
- Create and organize multi-agent AI workflows using CrewAI
- Design agent roles such as Supervisor, Researcher, and Action Executor
- Utilize LLM for decision-making and personalized task execution
- Create tool-based actions for data retrieval and API interaction
- Connect multiple agents for dynamic collaboration
- Configure agent prompts to manage their behavior and outputs
If you are interested in AI that actually performs tasks rather than just discussing them, this brief course is for you. You will learn to create AI agents that collaborate, delegate, and act using the intuitive structure of CrewAI.
We will start by defining roles for each agent, then link them with tools and actions that allow data retrieval, decision-making, and effective collaboration. You will progress from setting up simple workflows to organizing full-fledged AI systems.
By the end of the course, you will create a multi-agent AI interview coach powered by CrewAI!
