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Recommender System Course

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

What will I learn?

This Recommender System Course provides a quick, practical route to creating effective video recommendations. You'll learn to gather user behaviour signals such as views, likes, watch time, and searches, develop strong features, and manage sparsity. Design scalable pipelines, select suitable algorithms, adjust offline metrics, and conduct dependable A/B tests to increase engagement, retention, and session duration in actual products.

Elevify advantages

Develop skills

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

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 interest without needing to change platforms... I'm grateful 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 way videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and simple to use. The diversity of content and complementary videos really help with learning.
André Felipe
André FelipePrompt Engineering Student

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