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CrewAI 101: Building Multi-Agent AI Systems

BeginnerGuided Project

Build AI agent teams that divide complex problems between specialized experts using CrewAI. Create a collaborative system where research analysts uncover insights, content strategists craft compelling narratives, and designers create polished web presentations—all working together in a seamless workflow. This approach solves problems no single agent could handle, mimicking human organizations where specialists combine their expertise. In just 45 minutes, master this orchestration framework to develop sophisticated AI systems that transform workflow automation and decision support.

Language

  • English

Topic

  • Artificial Intelligence

Skills You Will Learn

  • AI Agents, Python, CrewAI, Generative AI, LLM

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 45 minutes

Platform

  • SkillsNetwork

Last Update

  • July 9, 2025
About this Guided Project
In today's rapidly evolving AI landscape, single agents often struggle to address complex, multifaceted challenges effectively. This guided project introduces you to CrewAI—a powerful framework for orchestrating teams of specialized AI agents that work collaboratively toward shared objectives.

Through hands-on implementation, you'll build a practical multi-agent system that analyzes AI advancements and creates polished content about them. Your CrewAI system will employ a sequential workflow where a research analyst investigates current AI trends, a content strategist transforms findings into engaging narratives, and a web designer creates accessible presentations—creating a streamlined pipeline from research to final output.


What you'll learn 

After completing this project, you will be able to:
  • Design specialized AI agents with distinct roles, backstories, and tools for targeted tasks
  • Construct sequential workflows that pass information seamlessly between agents
  • Monitor performance metrics including token usage and execution time
  • Build a complete fact-checking application from research to web presentation
  • Adapt multi-agent patterns for your own business and analytical use cases

Who should enroll 

This project is perfect for:
  • Developers seeking to build more sophisticated AI applications through agent collaboration
  • Data scientists looking to automate complex analytical workflows
  • AI enthusiasts who want to explore the next evolution in AI architecture
  • Business professionals interested in workflow automation and AI-driven decision support

What you'll need 

Before beginning this guided project, you should have:
  • Basic understanding of Python programming
  • Familiarity with fundamental AI concepts
  • Access to a modern web browser for the IBM Skills Network Labs environment

Why enroll 

By completing this project, you'll gain practical experience with CrewAI—an emerging framework that represents the next frontier in AI application development. The skills you acquire will enable you to design systems where specialized agents collaborate to tackle challenges in business automation, data analysis, content generation, and decision support. As organizations increasingly seek AI solutions for complex processes, the ability to orchestrate multi-agent systems will become an invaluable skill for developers and AI practitioners in virtually every industry.

Instructors

Kunal Makwana

Data Scientist

I’m a passionate Data Scientist and AI enthusiast, currently working at IBM on innovative projects in Generative AI and machine learning. My journey began with a deep interest in mathematics and coding, which inspired me to explore how data can solve real-world problems. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and leveraging cloud technologies to extract meaningful insights from complex datasets.

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Karan Goswami

Data Scientist

I am a dedicated Data Scientist and an AI enthusiast, currently working at IBM's Skills Builder Network. Learning how some simple mathematical operations could be used to make predictions and discover patterns sparked my curiosity, leading me to explore the exciting world of AI. Over the years, I’ve gained hands-on experience in building scalable AI solutions, fine-tuning models, and extracting meaningful insights from complex datasets. I'm driven by a desire to apply these skills to solve real-world problems and make a meaningful impact through AI.

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Contributors

Faranak Heidari

Data Scientist at IBM

Detail-oriented data scientist and engineer, with a strong background in GenAI, applied machine learning and data analytics. Experienced in managing complex data to establish business insights and foster data-driven decision-making in complex settings such as healthcare. I implemented LLM, time-series forecasting models and scalable ML pipelines. Enthusiastic about leveraging my skills and passion for technology to drive innovative machine learning solutions in challenging contexts, I enjoy collaborating with multidisciplinary teams to integrate AI into their workflows and sharing my knowledge.

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Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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