Retrieval-Augmented Generation (RAG) with Embeddings & Vector Databases

In this course, you will explore advanced AI engineering concepts, focusing on the creation, use, and management of embeddings in vector databases, as well as their role in Retrieval-Augmented Generation (RAG). You will start by learning what embeddings are and how they help AI interpret and retrieve information. Through hands-on exercises, you will set up environment variables, create embeddings, and integrate them into vector databases using tools like Supabase. As you progress, you will take on challenges that involve pairing text with embeddings, managing semantic searches, and using si…