- Course
- AI
Multi-modal RAGs
Learn how to extend text-only RAG systems into powerful multi-modal pipelines. This course teaches you to integrate text and images, optimize retrieval, and deliver accurate, trustworthy AI outputs.
What you'll learn
Multi-modal data is becoming increasingly critical in enterprise AI systems, yet traditional RAG pipelines fail when confronted with images, charts, and tables.
In this course, Multi-modal RAGs, you’ll learn to design and implement RAG systems that can seamlessly handle multiple modalities.
First, you’ll explore the challenges and requirements of multi-modal RAG systems and why semantic alignment is so important.
Next, you’ll build a multi-modal retrieval pipeline using embeddings, hybrid stores, and grounding techniques.
Finally, you’ll learn to optimize performance and generate outputs that combine text explanations with visual elements.
When you’re finished with this course, you’ll have the advanced skills and knowledge needed to design and deploy production-ready multi-modal RAG systems.
Table of contents
About the author
Eva Paunova is a Senior AI Research Scientist specializing in LLMs, trust, and evaluation. She helps learners build reliable AI systems with real-world impact.