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Recommender System Course

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

What will I learn?

This Recommender System Course provides a quick, practical route to developing high-impact 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 effective algorithms, tune offline metrics, and conduct reliable A/B tests to increase engagement, retention, and session length in actual products.

Elevify advantages

Develop skills

  • Design video recommenders: turn user behaviour into high-impact suggestions.
  • Engineer signals: convert raw logs into clean, weighted engagement features.
  • Build and tune models: apply CF, content-based, and hybrid recommenders quickly.
  • Evaluate systems: use MAP, NDCG, and A/B tests to boost 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 are saying

Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to switch 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 change chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the presentation style and video transcription, 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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