Overview
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Ready to build the next generation of AI applications? This specialization from IBM experts equips you with the skills to develop agentic AI systems using modern frameworks and workflow patterns.
You’ll start with LangGraph, creating agents that support memory, iteration, conditional logic, and retrieval-augmented generation (Agentic RAG).
Next, you’ll explore self-improving agents that use reflection and reasoning, and design multi-agent systems that collaborate through orchestration. With CrewAI, you’ll learn to structure agents, tasks, and tools into modular workflows that solve real-world problems.
Finally, you’ll expand your toolkit with frameworks like AG2 (AutoGen) and BeeAI, applying them to cases such as question answering, summarization, and conversation-driven applications. You’ll also study design patterns like sequential and routing to make systems scalable and reliable.
You will apply the concepts you’ve learned using hands-on labs to build Agentic systems powered by LLMs such as OpenAI GPT, Meta Llama, and IBM Granite.
By the end of this program, you’ll be able to compare frameworks, apply AI design patterns, implement orchestration, and build AI systems that support multi-agent collaboration and advanced workflows. These are the sought-after skills that employers look for in Software Developers, Machine Learning Engineers, Data Scientists, and GenAI Engineers.
Syllabus
- Course 1: Fundamentals of Building AI Agents
- Course 2: Agentic AI with LangChain and LangGraph
- Course 3: Agentic AI with LangGraph, CrewAI, AutoGen and BeeAI
Courses
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Are you ready to build AI that thinks, acts, and gets things done? In this course, you’ll learn how to design agents that go beyond language generation to reason, take action, and tackle real-world tasks using tools and data.  During the course, you'll explore the foundations of tool calling and chaining with LangChain. You’ll discover how to extend the capabilities of Large Language Models (LLMs) by connecting them with calculators, code, and external data sources. You'll learn how LLMs trigger tool use through LangChain Expression Language (LCEL) and look at manual tool calling for greater control and accuracy. Plus, you’ll explore built-in agents that can analyze data, create visualizations, and run SQL queries using natural language.  To get the most from this course, we recommend that you have Python programming skills, a basic understanding of LangChain, and familiarity with core AI concepts.  Whether you're building a chatbot or a smart assistant, if you’re looking to build the skills to create dynamic, intelligent, and goal-oriented AI systems, enroll today!
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Ready to build intelligent AI agents that can reason, improve, and collaborate? This hands-on course gives you the skills to build agentic AI systems using LangChain and LangGraph in just 3 weeks. You’ll design stateful workflows that support memory, iteration, and conditional logic. You’ll explore how to build self-improving agents using Reflection, Reflexion, and ReAct architectures, empowering your agents to reason about their outputs and refine them over time. Plus, you’ll work on guided labs where you’ll structure agent feedback, integrate external data, and generate context-aware responses through step-by-step reasoning. You’ll then develop collaborative multi-agent systems that coordinate tasks, retrieve relevant data, and solve complex problems using agentic RAG. Plus, you'll gain experience in agent orchestration, query routing, and governance strategies for building robust, scalable AI applications. By the end of the course, you’ll have built working prototypes of agentic systems and gained hands-on skills to design reliable, adaptable agents. Enroll today and get ready to power up your portfolio!
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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.
Taught by
Faranak Heidari, Joseph Santarcangelo, Karan Goswami, Kunal Makwana, Martin Keen, Tenzin Migmar and Wojciech 'Victor' Fulmyk