Vector Search with Relational Databases using PostgreSQL

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Vector Search with Relational Databases using PostgreSQL

This course is part of Vector Database Fundamentals Specialization

Instructors: SkillUp

Included with

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1 module

Gain insight into a topic and learn the fundamentals.

24 reviews

Intermediate level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

24 reviews

Intermediate level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Describe the principles of modeling vector data in Relational databases (RDBMS). 
Apply the commands necessary to store, retrieve, and query vectors efficiently in PostgreSQL. 
Implement indexing techniques and optimization strategies for enhancing vector search performance. 
Demonstrate, through hands-on labs, how to set up environments and perform vector searches using PostgreSQL.

Skills you'll gain

Tools you'll learn

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Assessments

3 assignments

Taught in English

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This course is part of the Vector Database Fundamentals Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There is 1 module in this course

With vector databases now powering business competitiveness through super-fast applications such as recommendation engines, it’s no surprise that the vector database market is set to grow 23% CAGR by 2032 (Markets and Markets).

This micro course gives aspiring data scientists, ML engineers, gen-AI engineers, software developers, and other data-oriented roles the in-demand skills for performing vector searches in relational databases. Businesses use vector search with relational databases to improve information retrieval via advanced similarity matching. You’ll gain hands-on experience working with PostgreSQL as your relational database platform and Python and JavaScript to vectorize data, create embeddings and collections, and load data, including bulk insertion techniques. Plus, you’ll provide similarity search recommendations using techniques such as cosine similarity. This micro course is part of the IBM Vector Database Fundamentals specialization, designed for professionals building on their NoSQL and relational database experience to work with vector databases. So, enroll today and get set to power your career with highly sought-after relational vector database skills.

Welcome to this module, where you’ll learn how to implement vector searches using relational databases. You’ll begin with a recap of RDBMS and then dive into the structures RDBMS uses to support vector data types and queries. You’ll apply what you know to perform similarity search tasks using special operators available in PostgreSQL. And, with a focus on PostgreSQL, you’ll learn how to create tsvector data, perform tsquery tasks, and perform bulk inserts using pg-vector for Node.js and psycopg2 for Python.

What's included

8 videos5 readings3 assignments6 app items5 plugins

8 videos Total 42 minutes

Course Introduction 2 minutes
Relational Databases: A Recap 7 minutes
Vector Embeddings in Relational Databases 8 minutes
RDBMS that Supports Vector Database Search 6 minutes
Adding Embedding Data to pgvector 6 minutes
Bulk Insert Methods for Vector Data 5 minutes
Performing Vector Data Queries 6 minutes
Course Summary 3 minutes

5 readings Total 12 minutes

Course Overview 3 minutes
Lesson Summary: PostgreSQL as a Vector Database 2 minutes
Summary 2: Implementing PostgreSQL as a Vector Database 4 minutes
Congratulations and Next Steps 2 minutes
Thanks from the Course Team 1 minute

3 assignments Total 27 minutes

Practice Quiz: PostgreSQL as a Vector Database 6 minutes
Practice Quiz: Implementation of PostgreSQL as Vector Database 6 minutes
Graded Quiz: Implementing Vector Search with Relational Databases 15 minutes

6 app items Total 225 minutes

Lab: Creating and Retrieving Data in PostgreSQL using Node.js 30 minutes
Lab: Creating and Retrieving Data in PostgreSQL Using Python 30 minutes
Lab: Creating a Vector DB in PostgreSQL using Python 30 minutes
Lab: Creating Vector Database in PostgreSQL with Node.js 60 minutes
Lab: Batch Loading and Querying with Node.js 45 minutes
Lab: Batch Loading and Querying with Python 30 minutes

5 plugins Total 55 minutes

Reading: How to Make the Most of this Course 5 minutes
Reading: Creating Indexes for Vector Search Optimization 15 minutes
Reading: Cloud Platforms that Support pgvector 5 minutes
Course Glossary: Implementing Vector Search with Relational Databases 15 minutes
Course Cheat Sheet: Implementing Vector Search with Relational Databases 15 minutes

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Instructors

SkillUp

128 Courses 435,858 learners

Offered by

SkillUp

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Reviewed on Oct 22, 2024

Such good and detailed course contents, very helpful.

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Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.