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Vector Database Projects: AI Recommendation Systems

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IntermediateCourse

In this course, you will apply your knowledge of vector databases, natural language processing, embeddings, and similarity searches to create database-backed recommendation systems in a practice project and a final capstone project using JavaScript and ChromaDB.This course is the last in a series of microcourses. Follow the link below to read about the series and see how this program can benefit you and advance your career.

Language

  • English

Topic

  • Database

Skills You Will Learn

  • Databases, Applied Machine Learning, MongoDB, Data Processing, API Gateway, Artificial Intelligence

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 5 Hours

Platform

  • Coursera

Last Update

  • May 30, 2025
About this Course
The global recommendation engine market is predicted to grow 37% annually through 2030 (Straits Times). The expertise to predict user preferences and drive engagement using AI recommendation system skills has become an essential business need and a highly sought-after skill using vector databases. 
In this IBM mini-course, you’ll create two shareable projects that demonstrate your proficiency and readiness to develop AI-powered recommendation systems.  
 
You’ll get step-by-step instructions to create a real-life inspired food ordering recommendation system using Chroma DB and Hugging Face models. For your final project, you’ll use Chroma DB or your choice of PostgreSQL, Cassandra, or MongoDB to create a real-life job search recommendation system. This will demonstrate your ability to generate embeddings and implement similarity searches using Hugging Face natural language processing (NLP) algorithms. 
 
Ready to start? Bring your vector, NoSQL, or relational database vector search skills to this course. If you don't already have these skills, you can attain these skills in other Vector Databases Fundamentals Specialization courses.  
 
Enroll today in this mini-course to advance your AI career!

Course Syllabus

  • Welcome
  • Introduction to Hugging Face
  • Practice project
  • Final project

Learning Objectives

  • Develop a recommendation system using the ChromaDB vector database and Hugging Face tools 
  • Generate vector embeddings using natural language processing algorithms
  • Perform similarity searches using vector embeddings 
  • Search a database using a PDF as the input query

Recommended Skills Prior to Taking this Course

This course is the culminating project course in the series linked above. We highly recommend that you take the previous courses before this one.
To get the most out of this course, you should be comfortable with the following:
Technologies:
  • JavaScript
  • ChromaDB
  • Git and GitHub
Concepts:
  • Vector embeddings
  • Natural language processing concepts
  • Recommendation systems
  • Similarity searches
If you take the previous courses in the series, you will learn what you need for success in this course.

Instructors

IBM Skills Network

IBM Skills Network Team

At IBM Skills Network, we know how crucial it is for businesses, professionals, and students to build hands-on, job-ready skills quickly to stay competitive. Our courses are designed by experts who work at the forefront of technological innovation. With years of experience in fields like AI, software development, cybersecurity, data science, business management, and more, our instructors bring real-world insights and practical, hands-on learning to every module. Whether you're upskilling yourself or your team, we will equip you with the practical experience and future focused technical and business knowledge you need to succeed in today’s ever-evolving world.

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