Recommendation System Course
This course provides practical skills in building, evaluating, and deploying video recommendation systems using collaborative filtering, matrix factorization, and hybrid methods, covering data processing, feature engineering, ranking metrics, A/B testing, and handling challenges like cold starts and biases.
from 4 to 360h flexible workload
certificate valid in your country
What will I learn?
This Recommendation System Course equips you with hands-on skills to design, assess, and roll out top-notch video recommenders. You'll sort and check interaction data, create strong features for users, items, and contexts, and use collaborative filtering, matrix factorisation, and hybrid approaches. Gain knowledge in ranking measures, A/B trials, ANN searches, oversight, and instant personalisation to deliver dependable, expandable recommendation setups.
Elevify advantages
Develop skills
- Build ready-for-use recommenders: from raw data to ranked top-N lists quickly.
- Create video-focused features: viewing habits, freshness, and content cues.
- Apply scalable ANN search and two-step retrieval for massive item collections.
- Assess and A/B test recommenders using ranking, CTR, and engagement measures.
- Manage cold starts, biases, and shifts with practical, business-oriented methods.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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