Multi-agent systems let generative AI go beyond single tasks, enabling teams of agents that can plan, reason, and collaborate to solve complex problems.
Design, Develop, and Deploy Multi-Agent Systems with CrewAI
Design, Develop, and Deploy Multi-Agent Systems with CrewAI
Instructor: Joe Moura
Access provided by Pepperdine University
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
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.
Skills you'll gain
- Artificial Intelligence and Machine Learning (AI/ML)
- Application Performance Management
- Continuous Monitoring
- Artificial Intelligence
- User Feedback
- Tool Calling
- Code Review
- Test Tools
- LLM Application
- Performance Metric
- System Monitoring
- Scalability
- Agentic systems
- Automation
- Integration Testing
- Business Software
- Generative AI Agents
- Workflow Management
- Prompt Engineering
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in English
Recently updated!
November 2025
See how employees at top companies are mastering in-demand skills
There are 4 modules in this course
In this module, you will design and develop single- and multi-agent systems from concept to prototype. You'll tune agent behavior using context engineering, study real-world use cases, and examine how these systems run in production. You will complete the graded quiz and Automatic Code Review graded programming assignment to pass the module.
What's included
10 videos3 readings1 assignment1 programming assignment2 ungraded labs
In this module, you'll learn to control agent behavior with guardrails, execution hooks, memory, and knowledge to guide richer decision cycles. You will build and integrate custom tools, and learn how the Model Context Protocol is expanding agent capabilities. You will complete the graded quiz and the Automatic Code Review graded programming assignment to pass the module.
What's included
7 videos1 reading1 assignment1 programming assignment2 ungraded labs
In this module, you will orchestrate agents in complex coordination pattern using sequential, parallel, hierarchical, hybrid, and async processes. You'll also implement Flows as a low-level control layer for orchestration. Finally, you'll learn how to monitor multi-agent systems with tracing, sampling, and observability tools, as well as train agents using human-in-the-loop feedback and structured evaluations. You will complete the graded quiz and Automatic Code Review Flow graded programming assignment to pass the module.
What's included
7 videos1 reading1 assignment1 programming assignment2 ungraded labs
In this module, you will explore how businesses adopt agents across industries and functions, from early chatbots to workflow co-pilots. You will analyze real deployments through case study interviews featuring leaders from Exa, Snyk, Weaviate, and AB InBev. You will complete the graded quiz to pass the module.
What's included
8 videos2 readings1 assignment
Instructor
Offered by
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
