Data Science Engineering Course
This course equips you with practical skills to build and deploy reliable machine learning models in production environments, focusing on real-world constraints and robust engineering practices.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This short, practical Data Science Engineering Course shows you how to frame ML problems, define KPIs, and respect real-world constraints while building reliable models. You will learn feature engineering, time-aware validation, class imbalance handling, and interpretability, then design robust pipelines, manage sensor data quality, automate training, and set up monitoring for stable, high-impact deployments.
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.What our students say
Your classes are perfect. I got the one-year package and finally have the chance to follow a range of topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...

Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the extra videos really help with learning.

Giulio CarloPrompt Engineering Student
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