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Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI

Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI

本课程是多个项目的一部分。

位教师：Faranak Heidari

2,906 人已注册

包含在 Coursera Plus 中

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3个模块

深入了解一个主题并学习基础知识。

4.9

（31 条评论）

中级等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

3个模块

深入了解一个主题并学习基础知识。

4.9

（31 条评论）

中级等级

推荐体验

1 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Design optimized AI systems by selecting and combining appropriate agentic frameworks and architectural patterns
Implement AI workflow patterns using agentic design principles and LangGraph
Build structured multi-agent workflows using CrewAI, including agents, tasks, and custom tools
Develop AI applications with BeeAI and design conversation-driven interactions using AG2 (AutoGen)

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要了解的详细信息

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该课程共有3个模块

Learn to build intelligent, autonomous multi-agent systems using powerful frameworks that can plan, collaborate, and execute complex tasks.

This course provides a structured approach to designing AI-powered systems using agentic design principles, orchestration strategies, and proven workflow patterns. You’ll explore popular frameworks such as LangGraph, CrewAI, BeeAI, and AG2 (formerly AutoGen), and learn how to select the right one for your needs. You’ll start with LangGraph, applying key design patterns such as sequential flows, routing, and parallelization to structure agent interactions. From there, you’ll move to CrewAI, where you’ll orchestrate agents, tasks, and tools, generate structured outputs using YAML and Pydantic, and extend capabilities with custom functions. Finally, you’ll explore BeeAI for orchestrating agents and workflows, and AG2 for creating multi-agent conversations and role-based collaboration. Through hands-on labs and real-world use cases, you will gain the skills needed to build scalable, maintainable, and efficient AI applications. Enroll today to gain cutting-edge agentic AI skills employers are looking for.

In this module, you’ll explore foundational concepts behind agentic frameworks and multi-agent systems, learning their role in AI application design. You’ll then examine essential design patterns that help structure AI workflows into modular and maintainable systems. Through hands-on labs using LangGraph, you'll gain experience implementing core workflow patterns that serve as building blocks for more complex AI solutions.

涵盖的内容

6个视频1篇阅读材料3个作业2个应用程序项目2个插件

6个视频总计41分钟

Course Introduction3分钟
Understanding Agentic AI and Open Source Frameworks8分钟
Building AI Agents with Open Source Frameworks8分钟
Essential Design Patterns for AI Systems8分钟
Orchestrator Design Pattern8分钟
Evaluator-Optimizer Design Pattern5分钟

1篇阅读材料总计4分钟

Course Overview4分钟

3个作业总计41分钟

Practice Quiz: Introduction to Agentic Frameworks 10分钟
Practice Quiz: Understand AI System Design Patterns10分钟
Graded Quiz: Agentic Frameworks and Design Patterns for Effective AI Systems21分钟

2个应用程序项目总计75分钟

Lab: Implement Workflow Patterns with LangGraph45分钟
Lab: Build LangGraph Design Patterns: Orchestration & Evaluation30分钟

2个插件总计7分钟

Reading: Helpful Tips for Course Completion5分钟
Cheat Sheet: Agentic Frameworks and Design Patterns for Effective AI Systems2分钟

This module introduces you to CrewAI and its core components, including agents, tasks, and crews. Through instructional videos and hands-on labs, you’ll learn to structure a CrewAI application, generate structured outputs, and extend capabilities with custom tools. You’ll gain practical experience by incrementally building CrewAI workflows and combining key features in an applied lab.

涵盖的内容

3个视频1篇阅读材料4个作业4个应用程序项目2个插件

3个视频总计26分钟

Design AI Agent Workflows with CrewAI 9分钟
CrewAI with Structured Outputs, YAML, and CrewBase Classes9分钟
Extending CrewAI with Custom Functions 7分钟

1篇阅读材料总计1分钟

Summary and Highlights 1分钟

4个作业总计51分钟

Practice Quiz: Introduction to CrewAI 10分钟
Practice Quiz: Structured Outputs in CrewAI10分钟
Practice Quiz: Functions and CrewAI10分钟
Graded Quiz: CrewAI Fundamentals and Advanced Applications 21分钟

4个应用程序项目总计180分钟

Lab: CrewAI 101 : Building Multi-Agent AI Systems45分钟
Lab: Create a Structured Meal & Grocery Planner with CrewAI45分钟
Lab: Agents with Tools vs. Tasks with Tools in CrewAI30分钟
Lab: Building your own AI Nutrition Coach using a Multi-Agent System and Multimodal AI60分钟

2个插件总计21分钟

Reading: Structured Outputs in CrewAI 6分钟
Cheat Sheet: CrewAI Fundamentals and Advanced Applications 15分钟

In this module, you’ll be introduced to two alternative agentic frameworks for building structured multi-agent AI applications: IBM’s BeeAI and AG2 (AutoGen). Through guided videos and hands-on labs, you’ll explore BeeAI’s architecture for creating agents and workflows, integrating tools, and managing memory. You’ll also examine AG2’s core components and learn how to configure multi-agent conversations using different patterns. By the end of the module, you will be able to implement basic agents using BeeAI and design structured, multi-agent conversations with AG2 for use cases like healthcare chatbots.

涵盖的内容

5个视频3篇阅读材料3个作业3个应用程序项目2个插件

5个视频总计38分钟

BeeAI: Introduction and Core Components9分钟
Building Agents with the BeeAI Framework8分钟
Introduction to AG2 (AutoGen) and its Key Elements9分钟
Extending AG2 with Tools and Structured Outputs6分钟
Course Wrap-Up 4分钟

3篇阅读材料总计4分钟

Summary and Highlights 2分钟
Congratulations and Next Steps1分钟
Team and Acknowledgments1分钟

3个作业总计41分钟

BeeAI Core Concepts and Architecture10分钟
Practice Quiz: AG2 (AutoGen) Core Concepts, Architecture, and Conversation Patterns10分钟
Graded Quiz: Alternative Agentic Frameworks: BeeAI and AG2 (AutoGen) 21分钟

3个应用程序项目总计195分钟

Lab: Building Agentic AI Systems with the BeeAI Framework120分钟
Lab: AG2 101 (AutoGen): Complete Tutorial45分钟
Lab: Build Multi-Agent Chatbot with AG2 (AutoGen) for Healthcare30分钟

2个插件总计25分钟

Reading: Agent Orchestration and Design Patterns in AG210分钟
Cheat Sheet: BeeAI & AG2 (AutoGen) Frameworks for Building Agentic AI Systems15分钟

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将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

授课教师评分

5.0 (6个评价)

Faranak Heidari

IBM

3 门课程11,430 名学生

提供方

IBM

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人们为什么选择 Coursera 来帮助自己实现职业发展

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学生评论

4.9

31 条评论

5 stars
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4 stars
6.06%
3 stars
3.03%
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已于 Sep 27, 2025审阅

Excellent course. Covers practical example of Agentic AI with LanGraph , CrewAI , AutoGen and BeeAI. Course also includes Lab implementation of all concepts covered.

已于 Sep 30, 2025审阅

A well paced and scoped "from zero to hero" curriculum; nice balance of theory and hands-on-aactiviies (both guided and independent); plus greaat cheat sheets you'll actually use!

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常见问题

By gaining hands-on experience with agentic design patterns and multi-agent frameworks like CrewAI, LangGraph, AG2, and BeeAI, you’ll be well-equipped for roles such as AI Workflow Engineer, Multi-Agent Systems Developer, Automation Architect, Generative AI Engineer, Machine Learning/AI Engineer, Software Developer, Data Scientist, or Data Engineer. These roles involve designing intelligent applications that automate complex workflows, collaborate across agents, and integrate with external systems.

Unlike traditional courses that emphasize linear coding logic, this course introduces you to AI agent orchestration and interaction design. You’ll learn to implement dynamic, goal-driven agents that can interact, make decisions, call tools, and manage tasks autonomously—transforming your approach from building static software to creating adaptive, collaborative AI ecosystems. This course provides a full overview of each framework and how they relate to Agentic AI. It covers a general overview of each Agentic framework, their pros and cons, and other relevant aspects.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.