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!

Prerequisites

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:

Concepts:

If you take the previous courses in the series, you will learn what you need for success in this course.

Course Objectives

After completing this course, you will be able to:

Course Outline

This course has one module with three lessons, listed below. We encourage you to set aside several hours in a single week to complete it. Consistency will best help you achieve your learning goals!

Congratulations on taking these steps to further your knowledge and career! Enjoy your journey.