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Building Your First Multi-Agent AI System with CrewAI · LearnSpace
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Building Your First Multi-Agent AI System with CrewAI

Курс от Edureka
Начальный≈ 11.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This program introduces you to Building Your First Agent with CrewAI, designed for developers and AI enthusiasts who want to design and implement intelligent multi-agent systems. You will begin by learning the foundational concepts of AI agents and agentic AI, exploring how autonomous agents reason, collaborate, and execute tasks. The course also introduces the CrewAI framework, explaining its architecture and how agents, tasks, crews, and flows work together to automate complex workflows. Next, you will explore LLM configuration and agent design techniques, including selecting suitable language models for different agent roles and applying effective prompt engineering strategies. You will learn how structured prompts guide agent behavior and improve reasoning quality. The course also covers context engineering, helping you design meaningful contextual inputs that allow agents to make better decisions and perform tasks more effectively. As you progress, you will learn how to build and execute multi-agent systems using CrewAI. Through guided demonstrations, you will design specialized agents, define structured tasks, and create collaborative workflows. You will also explore how crews coordinate agent activities, how outputs are structured, and how multi-agent systems can automate complex processes such as research, planning, and content creation. By the end of the program, you will be able to: - Explain the core principles of AI agents, agentic AI, and multi-agent systems. - Describe the CrewAI architecture, including agents, tasks, crews, and flows. - Configure development environments and tools required to build CrewAI projects. - Apply prompt engineering and context engineering techniques to guide agent reasoning. - Design structured workflows and execution flows for multi-agent systems. - Build and execute collaborative multi-agent crews to automate complex workflows. This program is ideal for developers, AI practitioners, and technical professionals interested in building intelligent agent systems. Prior experience with Python programming and basic AI concepts will help learners gain the most value from the course. Learners need a reliable internet connection, a modern web browser, and access to Python development tools. The course uses the CrewAI framework and LLM APIs, which do not require specialized hardware. Basic familiarity with Python and working with development environments is recommended. Join this course to learn how to design, build, and deploy multi-agent AI systems that can automate workflows, coordinate tasks, and power intelligent AI-driven applications.

Навыки, которые вы освоите

CrewAIAgentic systemsAgentic WorkflowsPrompt EngineeringAI WorkflowsContext EngineeringAI OrchestrationModel EvaluationLLM ApplicationPrompt PatternsDevelopment EnvironmentGenerative AI AgentsGenerative AILarge Language ModelingVirtual EnvironmentPython ProgrammingWorkflow Management

Программа курса

4 модулей · 76 учебных материалов

01Introduction to Multi-Agent AI Systems and CrewAI26 материалов

Introduction to AI Agents and Agentic AI

Specialization IntroductionВидеоCourse IntroductionВидеоCourse SyllabusЧтениеMarketing Team’s Struggle with Traditional AIВидео

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Edureka

Преподаватель курса

Building Your First Multi-Agent AI System with CrewAI
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Обучение откроется на Coursera
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Обучение на Coursera

≈ 11.6 ч

4 модулей

Язык: Английский

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

Часть программы вашего университета
Introduction to Agentic AIВидео
Core Concepts of Agentic AIВидео
Difference between AI Agents and Agentic AIВидео
Types of Agents in AIЧтение
Real-World Agentic AI Use CasesВидео
Practice Assignment: Introduction to AI Agents and Agentic AIЗадание

Multi-Agent Systems and the CrewAI Framework

Single-Agent vs Multi-Agent AI ArchitecturesВидеоHow do Multi-Agent Systems Work?ВидеоWhat is CrewAI?ВидеоUnderstanding CrewAI ArchitectureВидеоCrewAI vs Other AI Agent FrameworksВидеоBusiness Case for Multi-Agent AI SystemsЧтениеPractice Assignment: Multi-Agent Systems and the CrewAI FrameworkЗадание

Development Environment Setup for CrewAI

Preparing Your CrewAI Development EnvironmentВидеоDemonstration: Setting up Virtual Environment for Your Agentic SystemВидеоDemonstration: Installing CrewAI with uv Package ManagerВидеоDemonstration: Understanding Project Structure and File OrganizationВидеоBest Practices for Structuring and Managing AI Agent ProjectsЧтениеPractice Assignment: Development Environment Setup for CrewAIЗадание

Module Wrap-Up and Assessment

Module Summary: Introduction to Multi-Agent AI Systems and CrewAIЧтениеKnowledge Check: Introduction to Multi-Agent AI Systems and CrewAIЗаданиеEvaluating a Multi-Agent AI SolutionDIALOGUE
02Prompt, Context, and Flow Engineering for AI Agents23 материалов

Choosing and Configuring LLMs for Agents

LLM Providers and Model SelectionВидеоDemonstration: Configuring Models per Agent RoleВидеоDemonstration: Evaluating Cost, Latency, and Accuracy Trade-offsВидеоModel Selection Strategies for Agent-Based ApplicationsЧтениеPractice Assignment: Choosing and Configuring LLMs for AgentsЗадание

Prompt Engineering for AI Agents

Principles of Effective Prompt Engineering for AgentsВидеоCore Prompting TechniquesВидеоDemonstration: Writing prompts to guide agent behavior and toneВидеоDemonstration: Evaluating Prompt Impact Through Structured ComparisonВидеоDemonstration: Refining Prompts to Improve Agent ReasoningВидеоPrompt Engineering Best Practices for Agentic SystemsЧтениеPractice Assignment: Prompt Engineering for AI AgentsЗадание

Context and Flow Engineering for Agent Systems

Introduction to Context EngineeringВидеоFlow Engineering FundamentalsВидеоDemonstration: Designing High-Quality Context for AI AgentsВидеоDemonstration: Context Quality in Action – Signal vs NoiseВидеоDemonstration: Flow Engineering for Multi-Agent SystemsВидеоDemonstration: Architecting Execution Flows in Multi-Agent SystemsВидео

Module Wrap-Up and Assessment

Module Summary: Prompt, Context, and Flow Engineering for AI AgentsЧтениеKnowledge Check: Prompt, Context, and Flow Engineering for AI AgentsЗаданиеDesigning Effective Prompts and Agent WorkflowsDIALOGUE
03Building and Executing Multi-Agent Crews21 материалов

Designing AI Agents in CrewAI

Key Elements for High-Performance Agents in CrewAIВидеоDemonstration: Architecting Intelligence: Setting Up Your CrewAI ProjectВидеоDemonstration: Designing High-Performance Agents with YAML ConfigurationВидеоAgent Design Patterns and Common MistakesЧтениеPractice Assignment: Designing AI Agents in CrewAIЗадание

Task Definition and Structured Outputs

Understanding Tasks in CrewAIВидеоDemonstration: Designing High-Precision Research and Strategy TasksВидеоDemonstration: Building a Self-Executing and Self-Evaluating Campaign PipelineВидеоDemonstration: Engineering Structured Intelligence: Schemas, Hooks, and Execution LifecycleВидеоDemonstration: Intelligent Model Assignment and Structured Multi-Agent ExecutionВидеоTask Design and Output Structuring Best PracticesЧтениеPractice Assignment: Task Definition and Structured OutputsЗадание

Crew Assembly, Execution, and Collaboration

Agent Collaboration MechanismsВидеоDemonstration: Execution Modes and Output Inspection in main.pyВидеоDemonstration: Single, Batch, and Async Execution Modes in main.pyВидеоDemonstration: Running Your CrewAI System from the TerminalВидеоCollaboration and Orchestration Patterns for Multi-Agent SystemsЧтениеPractice Assignment: Crew Assembly, Execution, and CollaborationЗадание

Module Wrap-Up and Assessment

Module Summary: Building and Executing Multi-Agent CrewsЧтениеKnowledge Check: Building and Executing Multi-Agent CrewsЗаданиеDesigning and Deploying a Multi-Agent Crew with CrewAIDIALOGUE
04Course Wrap-Up and Assessment6 материалов

Course Wrap-Up and Assessment

Reflecting on Your AI Agent Building JourneyDIALOGUEPractice Project: Building a Multi-Agent Customer Support Assistant with CrewAIЧтениеEnd Course Knowledge Check: Building Your First AI Agent with CrewAIЗаданиеDesigning a Collaborative Multi-Agent Content Creation System Using CrewAIЗаданиеCourse SummaryВидеоDescribe Your Learning JourneyОбсуждение
Context and Flow Design Patterns for Agent SystemsЧтение
Practice Assignment: Context and Flow Engineering for Agent SystemsЗадание