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

Курс от DeepLearning.AI
Начальный≈ 21.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

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.

Навыки, которые вы освоите

Memory ManagementAgentic systemsContext EngineeringAutomationSystem MonitoringModel Context ProtocolAI OrchestrationAgentic WorkflowsArtificial IntelligenceLLM ApplicationLarge Language ModelingCrewAITool CallingContext ManagementWorkflow ManagementContinuous MonitoringArtificial Intelligence and Machine Learning (AI/ML)AI WorkflowsGenerative AI AgentsScalability

Программа курса

4 модулей · 52 учебных материалов

01Foundations of AI Agents17 материалов

Foundations of AI Agents

WelcomeВидеоCourse OverviewВидеоCourse SyllabusЧтениеWhat Are AI Agents?Видео

Учитесь у экспертов

Joe Moura

Founder and CEO

Design, Develop, and Deploy Multi-Agent Systems with CrewAI
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Новые знания — в удобное для вас время.

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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 21.9 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Испанский, Японский

Часть программы вашего университета
Use Cases for AI AgentsВидео
What Makes an AI Agent Intelligent?Видео
Building your first AI AgentЛабораторная
Planning Multi-Agent SystemsВидео
Building Multi-Agent SystemsЛабораторная
Multi-Agent Systems in ProductionВидео
Tactics for Debugging, Observing, OptimizingВидео
Use Cases: Multi-Agent Systems at ScaleВидео
The AI Agent Revolution and Why It's Happening NowВидео
Join the DeepLearning.AI ForumЧтение
Module 1 Lecture NotesЧтение

Graded Assignments

AI Agents and ApplicationsЗаданиеAutomatic Code ReviewПрограммирование
02 Working with AI Agents12 материалов

Working with AI Agents

Understanding AI Agent WorkflowsВидеоIncorporating Memory and KnowledgeВидеоControlling Agents with GuardrailsВидеоControlling Agents with Execution HooksВидеоImproving a Deep Research CrewЛабораторнаяUsing Tools in AgentsВидеоAdding Tools to Your Deep Research CrewЛабораторнаяAdopting Model Context ProtocolВидеоBuilding a Meeting Preparation Co-PilotВидеоModule 2 Lecture NotesЧтение

Graded Assignments

Decision Making, Tools and Model Context ProtocolЗаданиеAdding Functionality to the Automatic Code ReviewПрограммирование
03Managing Systems of AI Agents12 материалов

Managing Systems of AI Agents

CollaborationВидеоCommunicationВидеоBuilding Coordination PatternsЛабораторнаяUsing the A2A ProtocolВидеоOrchestrating Agents with FlowsВидеоBuilding a Deep Research FlowЛабораторнаяTactics for Building Reliable SystemsВидеоMonitoring and ObservabilityВидеоCI/CD for AgentsВидеоModule 3 Lecture NotesЧтение

Graded Assignments

Multi-Agent Systems, Safety & ReliabilityЗаданиеCreating a Flow for Automatic Code ReviewПрограммирование
04Applying AI Agents in Business 11 материалов

Applying AI Agents in Business

Applications Across IndustriesВидеоFinding Applications of AI AgentsВидеоApplying AI Agents: ExaВидеоApplying AI Agents: SnykВидеоApplying AI Agents: WeaviateВидеоApplying AI Agents: AB InBevВидеоThe Future of AI AgentsВидеоModule 4 Lecture NotesЧтение

Graded Assignment

Agents across Application Domains and Enterprises Задание

Wrap Up

ConclusionВидеоAcknowledgmentsЧтение