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Build intelligent multi-agent AI systems that plan, collaborate, and execute using CrewAI.
Instructor: CampusX
Language: Hinglish
Validity Period: 1095 days
This course teaches you how to design and build multi-agent AI systems using CrewAI, with a strong focus on creating a real, practical project: a tool / framework quick start guide powered by AI agents.
You begin by understanding the shift from large language models to AI agents—what agents are, how they are structured, and why agent-based systems are better suited for complex, multi-step problems like documentation, onboarding, and developer tooling.
Next, you move into hands-on work with CrewAI. You will define agents, tasks, and crews in code, control agent behavior using guardrails, and enforce structured outputs with Pydantic. These concepts are applied directly to the project, where different agents handle research, structure, writing, validation, and refinement of a quick start guide.
As the system grows, you learn how to orchestrate agents using sequential and hierarchical processes, choosing the right execution strategy based on task complexity. You then implement Retrieval-Augmented Generation (RAG) and Agentic RAG so agents can pull accurate, up-to-date information from external sources while generating the guide.
A key part of the course is learning flows in CrewAI. You will connect agents with custom Python logic, build conditional and router-based flows, and manage structured and unstructured state as the guide evolves across multiple steps.
The course concludes with a complete end-to-end system where multiple crews, processes, RAG, Agentic RAG, and flows work together to automatically generate a high-quality tool or framework quick start guide.
By the end of this course, you’ll be able to:
If you want to move beyond demos and learn how agentic AI is used to build real tools and frameworks, this course is for you.
Course Duration: 17+ hours