Vector Database Projects: AI Recommendation Systems

IBM · View on Coursera ↗

Taught by IBM Skills Network Team, Richa Arora

Data ScienceInformation TechnologyComputer Science

Coursera

4.1

headline rating

Starisk

4.0

Holds up

Small sample. Only 7 reviews were readable, so this score is a hint, not a verdict. Every other course page reads about 20 of the most-helpful reviews.

About the 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 t

The dissent

The most-upvoted critical review (no upvotes, 2.0★).

“Jedes Modul ist sehr oberflächlich und wiederholt sich bei jeder datenbank”
2.0 / 5

Read the full review on Coursera ↗

Coursera's 4.1 comes from 16 ratings. Of those, 25.0% are 1–2★.

Starisk reads the reviews learners voted most helpful, and weights each by the square root of its votes: a review with 80 upvotes counts about five times one with 2. Unvoted reviews are not skipped out of laziness — by this model they carry no evidence that other students endorsed them.

That measures what the most-endorsed reviews say, not “true quality.” The rating distribution above is the whole population, so you can see the sample next to it.

Reviews read on 23 Oct 2026.Read them on Coursera ↗