Vector Databases for RAG: An Introduction
Skills:
Vector Stores90%
Gain expertise in using vector databases and improve your data retrieval skills in this hands-on course!
During the course, you’ll explore the fundamental principles of similarity search and vector databases, learn how they differ from traditional databases, and discover their importance in recommendation systems and Retrieval-Augmented Generation (RAG) applications. You’ll also dive into key concepts such as vector operations and database architecture to develop a strong grasp of Chroma DB's functionality.
You’ll gain practical experience using Chroma DB, a leading vector database solution. And through interactive labs, you’ll learn to create collections, manage embeddings, and perform similarity searches with real-world datasets.
You’ll then apply what you’ve learned by creating a real-world recommendation system powered by Chroma DB and an embedding model from Hugging Face; an ideal project to demonstrate your understanding of how vector databases improve search and retrieval in AI-driven applications.
If you’re keen to gain expertise in using vector databases and similarity searches, both essential components of the RAG pipeline, then enroll today!
Watch on Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Vector Stores
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
Ever Wondered How to Make Your RAG More Effective?
Medium · RAG
Why StarRocks Is Better Than Elasticsearch for RAG and AI-Powered Vector Search Analytics
Medium · LLM
Production RAG: Shipping a RAG System Into an Enterprise Product
Medium · RAG
HyDE: Search With the Answer You Wish You Had
Medium · RAG
🎓
Tutor Explanation
DeepCamp AI