Multi AI Agent Systems with crewAI
by DeepLearning.AI
Build six working multi-agent crews in three hours, taught by CrewAI's founder.
Overview
Taught by Joao Moura, the founder and CEO of CrewAI, this three-hour DeepLearning.AI short course is the canonical introduction to the crewAI framework, an open-source Python library for orchestrating role-playing autonomous agents that has passed 56,000 GitHub stars. The course runs 18 video lessons interleaved with runnable notebooks, and is structured around six progressively harder build-alongs rather than theory: a research-and-write article crew, a multi-agent customer support automation, a customer outreach campaign that introduces tools, an event-planning automation, a financial-analysis crew that demonstrates agent-to-agent collaboration, and a crew that tailors job applications to a posting. Between each build, short conceptual lessons cover the key elements of an agent (role, goal, backstory), the mental framework Moura uses to decide how to decompose work across agents, what makes a tool usable by an agent, and how to write a well-defined task with a clear expected output. The framing throughout is CrewAI's own abstraction set, Crews for autonomous role-based delegation and Flows for event-driven control with state management and conditional branching, so the material maps directly onto the library's production API rather than a teaching toy. It assumes basic prompt engineering and some coding familiarity, and is free during the DeepLearning.AI platform beta; a completion accomplishment is available to PRO members.
At a Glance
- Topic
- Agentic
- Level
- Beginner
- Format
- Course
- Cost
- Free
- Duration
- ~3 hours, self-paced (18 video lessons plus quiz)
- Provider
- DeepLearning.AI
- Hands-on
- Yes — code/exercises
- Certificate
- Available
What You’ll Learn
- ✓Define agents with a role, goal and backstory that shapes their behaviour
- ✓Decompose a business process into tasks with explicit expected outputs
- ✓Build a research-and-write crew that drafts an article end to end
- ✓Wire external tools into agents and know which tool types exist
- ✓Automate a customer support workflow across multiple collaborating agents
- ✓Use agent-to-agent delegation for a multi-step financial analysis crew
- ✓Apply Moura's mental framework for deciding how many agents a job needs
Highlights
- •Taught by CrewAI's own founder and CEO, Joao Moura, rather than a third-party instructor
- •Six complete runnable crews instead of toy snippets: article writing, support, outreach, event planning, financial analysis, job applications
- •Backed by a framework at 56.6k GitHub stars and roughly 2,700 commits, so the API you learn is actively maintained
- •Concept lessons are interleaved with builds, so each abstraction arrives right before you need it
- •Free during the DeepLearning.AI platform beta and short enough to finish in one sitting
Who It’s For
Best For
- ✓Python developers building their first multi-agent system
- ✓Engineers evaluating CrewAI against LangGraph or AutoGen
- ✓Technical leads automating multi-step internal business workflows
- ✓Prompt engineers moving from single-LLM calls to agent teams
Prerequisites
- •Basic prompt engineering: you should be comfortable writing and iterating on prompts
- •Some Python familiarity, since the labs are Jupyter notebooks
- •No machine learning or deep learning background is required
FAQ
What is Multi AI Agent Systems with crewAI?
A three-hour DeepLearning.AI short course, taught by CrewAI founder and CEO Joao Moura, that takes you from a single LLM call to teams of role-playing agents that delegate work to each other. You build six complete crews covering article research and writing, customer support, outreach, event planning, financial analysis and job-application tailoring, and finish able to decompose a real business process into agents, tasks and tools using the crewAI Python library.
Is Multi AI Agent Systems with crewAI free?
Multi AI Agent Systems with crewAI is free to access.
What level is Multi AI Agent Systems with crewAI for?
Multi AI Agent Systems with crewAI is aimed at a beginner audience. Recommended background: Basic prompt engineering: you should be comfortable writing and iterating on prompts, Some Python familiarity, since the labs are Jupyter notebooks, No machine learning or deep learning background is required.
How long does Multi AI Agent Systems with crewAI take?
Expect roughly ~3 hours, self-paced (18 video lessons plus quiz). Most learners work through it at their own pace.
What will I learn from Multi AI Agent Systems with crewAI?
You'll learn: Define agents with a role, goal and backstory that shapes their behaviour; Decompose a business process into tasks with explicit expected outputs; Build a research-and-write crew that drafts an article end to end; Wire external tools into agents and know which tool types exist; Automate a customer support workflow across multiple collaborating agents; Use agent-to-agent delegation for a multi-step financial analysis crew; Apply Moura's mental framework for deciding how many agents a job needs.
Topics
Sources
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