It is aimed at learners who already know the basic role of a large language model.
About this course
Study retrieval-augmented generation through IBM explainers on document retrieval, vector search and agentic workflows. This free course focuses on choosing a retrieval approach and understanding why RAG can fail with complex information. It is aimed at learners who already know the basic role of a large language model.
What you can learn
- Retrieval-augmented generation
- Sparse and dense retrieval
- Hybrid search
- Document extraction
- Multimodal RAG
- Retrieval evaluation
Course at a glance
| Provider | IBM |
|---|---|
| Platform | YouTube · IBM Technology |
| Access | Free Video |
| Level | Intermediate — WikiFree audience assessment |
| Language | English |
| Selected lessons | 23 |
| Video duration | 3h 22m · allow extra time for reflection and practice |
| Details checked | 9 October 2026 |
Inside the course
Compare RAG with direct model context and agentic approaches. Explore GraphRAG, multimodal and chunkless retrieval, then connect Docling, unstructured data and hybrid retrieval to the challenge of producing grounded answers.
Try this learning exercise
Choose a small collection of public documents and write five questions with known supporting passages. Plan how you would compare sparse, dense and hybrid retrieval using relevance and source coverage, without needing to deploy a paid service.
How to follow the course
Choose a lesson from the list or search for a specific topic. Use Previous and Next to continue, and mark lessons complete as you go. Progress is saved in this browser without a WikiFree account.
Each course retains its relevant lessons, including videos also used in another course. Numbered series follow their original lesson or part order. Only reviewed advertisements, unrelated items and identical repeated playlist entries are excluded. Source recordings may have been made at different times.
Free access, requirements and certificates
The selected public YouTube videos are free to watch. No paid subscription, payment card or examination is required for this video learning path. WikiFree independently organizes IBM Technology explainers and tutorials for self-paced study. This listing is not an official IBM qualification and does not include an IBM certificate, graded assignment or instructor feedback.
Familiarity with LLMs and basic data processing is helpful. This course explains approaches; it does not supply a hosted vector database or graded project.
Official IBM Technology playlist source ↗
Use this course in a learning path
- Free RAG Retrieval Foundations Learning PathCourse resource in this path
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Intermediate
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Free RAG Course: Retrieval, Vector Search and AI Agents | Intermediate | Retrieval-augmented generation · Sparse and dense retrieval · Hybrid search | 3h 22m of video; practice time is additional |
| Free RAG Course: Retrieval, Vector Search and Multimodal Data | Intermediate | Explain the retrieval stage of RAG · Design a retrieval system and vector index · Consider index scale and multimodal data | 2h 43m of video; practice time is additional |
| Free AI App Development Course: Local LLMs and RAG | Intermediate | Local LLM inference · RAG application patterns · AI tool calling | 8h 7m of video; practice time is additional |
| Free Generative AI with JavaScript Course: LLMs and RAG | Intermediate | Understand LLMs and prompt design · Use retrieval to improve answer relevance · Explore LangChain.js and local model workflows | 1h 43m of video; practice time is additional |
Provider: IBM. Videos play from the IBM Technology channel on YouTube.
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