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IBM

Building AI Agents and Agentic Workflows

IBM via Coursera Specialization

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

Taught by

Faranak Heidari, Joseph Santarcangelo, Karan Goswami, Kunal Makwana, Martin Keen, Tenzin Migmar and Wojciech 'Victor' Fulmyk

Reviews

4.7 rating at Coursera based on 222 ratings

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