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DeepLearning.AI

Design, Develop, and Deploy Multi-Agent Systems with CrewAI

DeepLearning.AI via Coursera

Overview

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Multi-agent systems let generative AI go beyond single tasks, enabling teams of agents that can plan, reason, and collaborate to solve complex problems. In this course, you’ll learn how to build multi-agent systems that automate complex, end-to-end workflows. You’ll create intelligent agent teams that plan, reason, and collaborate using tools, memory, and guardrails, and learn how to scale them for production. Across four modules, you’ll build practical applications including an automated code reviewer, a meeting co-pilot, and a deep researcher, each showcasing real-world design patterns for agent collaboration. You’ll monitor and debug agent performance using traces, evaluate behavior with LLM-as-a-Judge, and apply best practices for continuous improvement in production. By the end, you’ll be able to implement custom multi-agent systems that perform reliably, deliver measurable outcomes, and scale to thousands of users.

Syllabus

  • Foundations of AI Agents
    • 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.
  • Working with AI Agents
    • 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.
  • Managing Systems of AI Agents
    • 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.
  • Applying AI Agents in Business
    • 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.

Taught by

Joe Moura

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