Vector Databases for RAG: An Introduction

О курсе

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!

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Wojciech 'Victor' Fulmyk

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IBM Skills Network Team

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