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Data Science Engineering Course

Data Science Engineering Course
flexible workload of 4 to 360h
valid certificate in your country

What will I learn?

This practical Data Science Engineering Course teaches framing ML problems, defining KPIs, respecting real-world constraints, feature engineering, time-aware validation, class imbalance handling, interpretability, robust pipelines, sensor data quality management, automated training, and monitoring for stable deployments. Gain hands-on expertise for high-impact ML solutions.

Elevify advantages

Develop skills

  • Production ML design: frame KPIs, constraints, and targets for real systems.
  • Robust data pipelines: validate schemas, handle drift, and clean sensor streams.
  • Advanced feature engineering: build temporal, rolling, and cross-machine signals.
  • Model training & evaluation: tune GBMs/logistic models with business metrics.
  • MLOps automation: deploy, monitor, retrain, and rollback models with confidence.

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 classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... I appreciate everything you do, I've already recommended you to others...
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 the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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