At a Glance

Name: Build Agentic and Multi-Agent Systems in Python using BeeAI
Price: Free CAD
Rating: 5.0 (4 reviews)
Author: wojciech_fulmyk, jianping_ye

Build tool calling agents, ReAct agents, and human-in-the-loop multi-agent systems using OpenAI's GPT, IBM Granite, and Meta's Llama in the BeeAI Framework. This comprehensive, hands-on project requires no prior experience with BeeAI and takes you from initial setup to building intelligent systems for cybersecurity, business planning, and travel automation.

In the age of intelligent automation, building AI agents that can reason, act, and collaborate is no longer a futuristic concept; it is a practical necessity. Whether you're working in cybersecurity, business strategy, or travel planning, agentic systems offer a powerful way to automate complex workflows, integrate with external tools, and deliver human-like decision-making.

This project introduces you to the BeeAI Framework, a cutting-edge, open-source platform developed under the Linux Foundation AI and backed by IBM Research. BeeAI is built for production-grade agent development, offering robust support for multiple LLM providers such as OpenAI and watsonx.ai, which give you access to popular models including OpenAI's GPT, IBM Granite, and Meta’s Llama.

With BeeAI, you’ll learn to build intelligent systems that go far beyond simple chatbots—systems that can reason, act, and collaborate, even with human oversight. Whether you're automating cybersecurity analysis, planning business strategies, or coordinating travel, BeeAI equips you with the tools to build real-world, multi-agent AI systems that are flexible, scalable, and ready for deployment.

By completing this hands-on guided project, you’ll gain the skills to build intelligent agents and multi-agent systems, even if you’ve never used BeeAI before.

A Look at the Project Ahead

This project takes you from foundational concepts to advanced multi-agent architectures. You’ll build intelligent systems that solve real problems in cybersecurity, business planning, and travel automation. Along the way, you’ll learn how to integrate tools, enforce reasoning patterns, and include human oversight in your agents.

By the end of this guided project, you will be able to:

Design and build intelligent AI agents that can interact naturally, perform tasks, and make decisions based on structured reasoning.
Integrate external tools and data sources into your agents to enhance their capabilities, including research, calculations, and weather forecasting.
Create collaborative multi-agent systems where specialized agents work together to solve complex problems through coordinated workflows.
Implement human oversight and control mechanisms to ensure agents operate safely and transparently in production environments.

What You'll Need

To get started with this guided project, you’ll need:

Basic Python programming knowledge
General understanding of AI agents and LLMs (helpful but not required)
A modern browser, such as a current version of Chrome, Edge, Firefox, Safari, or Internet Explorer
No prior experience with BeeAI is required: everything is covered step-by-step

Offered By: IBMSkillsNetwork

Build Agentic and Multi-Agent Systems in Python using BeeAI

At a Glance

A Look at the Project Ahead

What You'll Need