Vector Database Projects: AI Recommendation Systems

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 objectives

• equip students with the skills to use vector databases for recommendation systems
• provide step-by-step project guidance to enhance practical understanding