Building Multimodal Search and RAG

Building Multimodal Search and RAG: Overview & Verdict

Learn how to build multimodal search and RAG systems. RAG systems enhance an LLM by incorporating proprietary data into the prompt context. Typically, RAG applications use text documents, but, what if the desired context includes multimedia like images, audio, and video? This course covers the technical aspects of implementing RAG with multimodal data to accomplish this. 1. Learn how multimodal models are trained through contrastive learning and implement it on a real dataset. 2. Build any-to-

Enrollment through Coursera includes the Q&A thread, where earlier students have already answered most of the questions newcomers run into.

It is taught by DeepLearning.AI, delivered in en — useful context when you are deciding whether Building Multimodal Search and RAG fits the time you have this week.

What you need before starting

• • A free Coursera account (takes under a minute to create)
• • A laptop, tablet or phone with a stable internet connection
• • Willingness to pause the video and repeat each exercise yourself

About DeepLearning.AI

DeepLearning.AI teaches Building Multimodal Search and RAG. The lessons follow a consistent structure and the Q&A section stays active, which is a good signal of ongoing support.

Our verdict: For anyone starting out in ai & machine learning, this is the cheapest low-risk way to test whether the subject suits you. Enroll now even if you plan to start later — access stays with your account after the coupon expires.