IBM · on Coursera

IBM RAG and Agentic AI Professional Certificate

4.6(964) on Coursera·98K enrolled
Advanced 24 hours English Professional Certificate
Our recommendation
An advanced, hands-on route into the two most in-demand GenAI skills: production RAG and autonomous agents. Across ten courses you build with the frameworks teams actually use — LangChain, LangGraph, CrewAI, AutoGen and the Model Context Protocol — rather than staying at the prompting level. Best once you already have Python and some LLM exposure.

Good for: Developers who already code and want to build production RAG systems and AI agents, backed by an IBM credential.

Less suitable if: You're new to Python or large language models — build those foundations first.

Skills you'll gain

RAGAI agentsLangChainLangGraphVector databasesTool callingPrompt engineeringAI orchestration

Is this course right for you?

A good fit if you…

You already write Python and know LLM basics
You want to build, not just understand, RAG and agents
You value an IBM-backed credential

Consider something else if you…

You're a complete beginner to AI
You only need prompting or AI literacy
You want vendor-neutral theory over hands-on frameworks

Requirements: Working PythonBasic familiarity with large language models

Realistic time: ~24 hours across a 10-course series, self-paced (about 2 months at a few hours a week)

About this course

The IBM RAG and Agentic AI Professional Certificate is a ten-course series that goes past prompting into the engineering work behind real GenAI products — retrieval-augmented generation grounded in vector databases, and multi-agent systems that plan, call tools and act. You build with the frameworks teams actually use: LangChain, LangGraph, CrewAI, AutoGen (AG2), BeeAI and the Model Context Protocol (MCP).

What you'll learn

Build production RAG pipelines grounded in vector databases
Design multi-agent systems that plan and call tools
Work with LangChain, LangGraph, CrewAI and AutoGen
Use the Model Context Protocol (MCP) to connect agents to tools
Apply prompt engineering and multimodal prompting in practice
Address AI security and orchestration in agentic apps

This course includes

24h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language

What it costs

You can audit the individual courses free on Coursera. The professional certificate requires a paid Coursera subscription (around $49/month or Coursera Plus), so cost depends on how fast you finish.

Comparison · LBS

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Prices & availability can change — confirm on the provider's site. We're not affiliated with any single provider.

Is the certificate recognised?

The certificate is issued by IBM and hosted on Coursera. It's a solid professional-development signal for GenAI engineering roles, though employers still weigh your projects and GitHub most heavily.

Instructor

IS
IBM Skills Network
Coursera instructor

The IBM Skills Network is IBM's education arm, which builds hands-on, lab-driven courses drawn from how IBM's own practitioners work — the reason its GenAI content leans practical rather than purely conceptual.

About this provider

CO
Coursera
University-backed online learning platform. 142M learners, 7,000+ courses from 325+ institutions.
Visit Coursera

Frequently asked questions

If you already code, yes — it's built around the exact frameworks that show up in agentic-AI job postings (LangChain, LangGraph, CrewAI, AG2) and it's genuinely hands-on. It's an advanced certificate, not a first AI course, and on its own it's a stepping stone: pair it with a project portfolio.
This is an advanced series, so working Python and prior exposure to machine learning / LLMs are real requirements, not nice-to-haves. Complete beginners should do an intro LLM or generative-AI course first, otherwise the pace will be tough.
DeepLearning.AI spans beginner to advanced and leans conceptual; this IBM certificate is narrower and more framework-heavy, focused on building production RAG and multi-agent systems with named tools. If you want depth on the engineering frameworks specifically, IBM's is the more targeted path.
LangChain, LangGraph, CrewAI, AG2 (AutoGen), BeeAI and the Model Context Protocol (MCP), plus vector databases for RAG — the stack teams use to build and orchestrate agents rather than a single library.
You can audit the individual courses free on Coursera; the professional certificate needs a Coursera subscription (around $49/month or Coursera Plus). It's a ten-course series most people finish in roughly two months at a few hours a week, self-paced.
Paid
Free to audit · paid certificate
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