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DeepLearning.AI

Vector Databases: from Embeddings to Applications

  • up to 1 hour
  • Intermediate

This course provides a comprehensive understanding of vector databases and their applications in various fields such as NLP, image recognition, and recommender systems. Learn to build efficient, practical applications including hybrid and multilingual searches without needing to train or fine-tune an LLM yourself.

  • Vector databases
  • Embeddings
  • Search techniques
  • Algorithms for fast searches
  • GenAI applications

Overview

In this course, you will gain the knowledge to make informed decisions about when to apply vector databases to your applications. You will explore how to use vector databases and LLMs to gain deeper insights into your data, build labs that show how to form embeddings, and use several search techniques to find similar embeddings. Additionally, you will explore algorithms for fast searches through vast datasets and build applications ranging from RAG to multilingual search.

  • Web Streamline Icon: https://streamlinehq.com
    Online
    course location
  • Layers 1 Streamline Icon: https://streamlinehq.com
    English
    course language
  • Self-paced
    course format
  • Live classes
    delivered online

Who is this course for?

Developers

Anyone who’s interested in understanding and applying vector databases in their applications.

Data Scientists

Professionals looking to enhance their knowledge in vector databases and their applications in various fields.

AI Enthusiasts

Individuals keen on learning about the integration of vector databases with LLMs and their practical applications.

This course offers key benefits such as understanding vector databases and their applications in various fields. It covers main topics like embeddings, search techniques, and algorithms for fast searches. Ideal for developers, data scientists, and AI enthusiasts, this course will help you build efficient, practical applications and advance your career.

Pre-Requisites

1 / 3

  • Basic understanding of databases

  • Familiarity with machine learning concepts

  • Experience with programming languages like Python

What will you learn?

Introduction to Vector Databases
Understand the basics of vector databases and their importance in various fields.
Embeddings and Their Applications
Learn how embeddings capture the meaning of data and gauge the similarity between different pairs of vectors.
Building Labs for Embeddings
Hands-on labs to form embeddings and use several search techniques to find similar embeddings.
Search Algorithms
Explore algorithms for fast searches through vast datasets.
Developing GenAI Applications
Build applications ranging from Retrieval Augmented Generation (RAG) to multilingual search.

Meet your instructor

  • Sebastian Witalec

    Head of DevRel, Weaviate

    Sebastian Witalec is an instructor at DeepLearning.AI and the Head of DevRel at Weaviate. He is based in Bielsko-Biala, Poland.

Upcoming cohorts

  • Dates

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