IBM
Building AI Agents and Agentic Workflows Specialization
IBM

Building AI Agents and Agentic Workflows Specialization

Build Autonomous Applications with AI Agents. Master Agentic AI with multi-agent frameworks such as LangGraph, CrewAI, BeeAI, and AG2 (AutoGen)

Wojciech 'Victor' Fulmyk
Faranak Heidari
Kunal Makwana

Instructors: Wojciech 'Victor' Fulmyk

Included with Coursera Plus

Get in-depth knowledge of a subject

(37 reviews)

Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject

(37 reviews)

Intermediate level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers

What you'll learn

  • Develop agentic AI applications that integrate tools, support reasoning, and improve performance through reflection

  • Design AI agents with LangGraph using agentic AI design principles such as memory, iteration, RAG, and workflow patterns

  • Orchestrate agentic multi-agent systems with CrewAI for collaboration, coordination, and workflows

  • Build conversation-driven agentic AI assistants with BeeAI and AG2; compare AI frameworks for real-world use case applicability

Overview

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
Recently updated!

August 2025

32 practice exercises

Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from IBM

Specialization - 3 course series

What you'll learn

  • Develop AI agents that can reason and perform tasks independently

  • Implement tool calling and chaining to create structured AI workflows

  • Utilize built-in LangChain agents to analyze data, generate visualizations, and execute database queries

  • Apply best practices in prompt engineering and tool calling to enhance AI agent performance

Skills you'll gain

LangChain, Tool Calling, LLM Application, Artificial Intelligence and Machine Learning (AI/ML), Generative AI Agents, Application Development, Agentic systems, and Software Development

What you'll learn

  • Build agentic AI systems using LangChain and LangGraph to support memory, iteration, and conditional logic

  • Design and implement self-improving agents using Reflection, Reflexion, and ReAct architectures

  • Apply agent orchestration techniques to build collaborative multi-agent systems

  • Implement agentic RAG systems that route queries and support retrieval-enhanced reasoning

Skills you'll gain

LangGraph, Agentic systems, LangChain, Generative AI Agents, Generative AI, LLM Application, Software Development, Collaborative Software, Python Programming, Responsible AI, Data Science, System Design and Implementation, Artificial Intelligence and Machine Learning (AI/ML), and Real Time Data

What you'll learn

  • Design optimized AI systems by selecting and combining appropriate agentic frameworks and architectural patterns

  • Implement AI workflow patterns using agentic design principles and LangGraph

  • Build structured multi-agent workflows using CrewAI, including agents, tasks, and custom tools

  • Develop AI applications with BeeAI and design conversation-driven interactions using AG2 (AutoGen)

Skills you'll gain

Agentic systems, Generative AI Agents, Software Design Patterns, Data Validation, LLM Application, Application Design, Tool Calling, and Large Language Modeling

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Wojciech 'Victor' Fulmyk
IBM
8 Courses85,046 learners
Faranak Heidari
IBM
3 Courses13,223 learners

Offered by

IBM

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