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Data Science and Engineering Course

Data Science and Engineering Course
4 to 360 hours flexible workload
valid certificate in your country

What will I learn?

Master the full lifecycle of recommendation systems with this practical Data Science and Engineering Course. Learn to explore interaction logs, design robust feature pipelines, choose the right models and metrics, and run reliable experiments. Build scalable deployment, monitoring, and alerting workflows, while applying strong privacy, security, and documentation practices to deliver measurable product impact fast.

Elevify advantages

Develop skills

  • Production-grade recommender features: design, validate, and prevent leakage fast.
  • Model selection for ranking: pick, tune, and evaluate AUC, precision@k, NDCG.
  • Scalable ML pipelines: build feature stores, ETL, and real-time serving flows.
  • MLOps for recommenders: deploy, monitor drift, A/B test, and auto-rollback safely.
  • Business-first problem framing: turn engagement goals into measurable ML targets.

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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