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Recommender System Course

Recommender System Course
4 to 360 hours of flexible workload
certificate valid in your country

What Will I Learn?

This Recommender System Course provides a quick, practical way to build effective video recommendations. Learn to capture user behaviour signals such as views, likes, watch time, and searches, engineer robust features, and manage sparsity. You will design scalable pipelines, select suitable algorithms, tune offline metrics, and conduct reliable A/B tests to improve engagement, retention, and session length in actual products.

Elevify Advantages

Develop Skills

  • Design video recommenders: transform user behaviour into impactful suggestions.
  • Engineer signals: convert raw logs into clean, weighted engagement features.
  • Build and tune models: apply CF, content-based, and hybrid recommenders efficiently.
  • Evaluate systems: use MAP, NDCG, and A/B tests to enhance CTR and watch time.
  • Ship to production: design scalable pipelines, retraining, and cold-start flows.

Suggested Summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can switch chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.
André Felipe
André FelipePrompt Engineering Student

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