Looking to level up your career by mastering the tools behind the latest multi-agent AI systems? This hands-on course teaches you how to design and build intelligent, collaborative AI workflows using cutting-edge frameworks like CrewAI, LangGraph, AG2 (AutoGen), and IBM’s BeeAI.
Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI
Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI
This course is part of IBM RAG and Agentic AI Professional Certificate
Instructors: Faranak Heidari
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
8 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Apply agentic AI principles using LangGraph, CrewAI, AutoGen, and BeeAI to design scalable AI systems
Analyze foundational AI design patterns and their implementation in LangGraph
Construct multi-agent systems using CrewAI by configuring agents and tasks
Develop AI-driven applications using BeeAI and AutoGen to create intelligent, conversation-driven solutions
Skills you'll gain
- Automation
- Generative AI
- Artificial Intelligence
- Software Design Patterns
- Agentic systems
- Generative AI Agents
- Artificial Intelligence and Machine Learning (AI/ML)
- ChatGPT
- Large Language Modeling
- Application Frameworks
- OpenAI
- Prompt Engineering
- Systems Design
- Health Technology
- Software Design
- Software Architecture
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
7 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your Software Development expertise
This course is part of the IBM RAG and Agentic AI Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from IBM
There are 3 modules in this course
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.
What's included
3 videos1 reading3 assignments2 app items2 plugins
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.
What's included
3 videos1 reading4 assignments4 app items2 plugins
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.
What's included
2 videos2 readings2 app items1 plugin
Earn a career certificate
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Frequently asked questions
By mastering 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, or Technical Product Manager. These roles involve designing intelligent applications that automate complex workflows, collaborate across agents, and integrate with external systems.
Not at all! While familiarity with Python is recommended, this course is designed to be approachable for developers without prior machine learning experience. You’ll focus on architecting AI systems using frameworks and tools, rather than training models, making it ideal for software developers looking to build intelligent, agent-driven applications.
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.
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Financial aid available,