Gain expertise in using vector databases and improve your data retrieval skills in this hands-on course! Start by exploring the fundamental principles of similarity search and vector databases, understanding how they differ from traditional databases, and recognizing their importance in recommendation systems and Retrieval-Augmented Generation (RAG) applications.
Vector Databases for RAG: An Introduction
Vector Databases for RAG: An Introduction
This course is part of IBM RAG and Agentic AI Professional Certificate
Instructors: IBM Skills Network Team
Included with 
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
1 hour to complete
Flexible schedule
Learn at your own pace
What you'll learn
Differentiate between vector databases and traditional databases based on their functionality and use cases
Execute fundamental database operations in ChromaDB, including updating, deleting, and managing collections
Understand and apply similarity search techniques, both manually and with ChromaDB, and develop recommendation systems using these techniques
Develop a thorough and comprehensive understanding of key internal mechanisms within RAG
Skills you'll gain
Details to know
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Assessments
2 assignments
Taught in English
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Build your Data Management expertise
This course is part of the IBM RAG and Agentic AI Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate from IBM
There are 2 modules in this course
This module explores the transformative role of vector databases in modern data management systems. Participants will learn how vector databases serve as the foundation of recommendation systems and how they differ from traditional databases in storing and managing vector data. Various vector database types and their specific applications will be examined, with a special focus on Chroma DB. Insights into Chroma DB architecture, common coding practices for its operations, and hands-on skills in performing basic vector operations will be provided. Moreover, similarity search will be thoroughly explained, with hands-on labs that perform similarity searches manually and using Chroma DB.
What's included
5 videos1 reading1 assignment5 plugins
This module explores the connections between vector databases, similarity search, recommendation systems, and Retrieval-Augmented Generation (RAG), while also providing instruction on essential database operations using Chroma DB. By analyzing employee data and building a food search recommendation system using hands-on labs, participants will gain a deeper understanding of both recommendation systems and Chroma DB. Moreover, the module highlights the critical role vector databases and similarity searches play within RAG systems.
What's included
1 reading1 assignment
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