ML Engineering Course
Master real-world ML engineering: design data pipelines, build feature stores, train and deploy recommendation models, and scale low-latency systems with robust monitoring, cost optimization, and production-ready architectures for modern tech teams.
flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
The ML Engineering Course shows you how to build real-time recommendation systems from end to end. Learn data collection, schema design, feature stores, and scalable storage, then move into feature engineering, training pipelines, and model selection. You also master serving architectures, monitoring, experimentation, and cost optimization so you can ship reliable, high-impact ML products quickly and confidently.
Elevify advantages
Develop skills
- Production ML pipelines: design robust data, feature, and training workflows fast.
- Real-time recommenders: build low-latency, scalable ranking and retrieval APIs.
- Feature engineering at scale: create batch and streaming features for impact.
- ML deployment & MLOps: ship, version, and roll back models with confidence.
- Monitoring ML systems: track drift, KPIs, and reliability in live environments.
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
Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change platforms... I'm grateful for everything you do, I've already recommended you to other people...
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 FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.
André FelipePrompt Engineering Student
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