ML Engineering Course
This course equips you with practical skills to engineer and deploy machine learning systems, focusing on building scalable recommendation engines and implementing MLOps best practices.

from 4 to 360h flexible workload
certificate valid in your country
What will I learn?
The ML Engineering Course teaches you how to build real-time recommendation systems from start to finish. You will learn about data collection, schema design, feature stores, and scalable storage, then progress to feature engineering, training pipelines, and model selection. You will also gain expertise in serving architectures, monitoring, experimentation, and cost optimisation to deliver reliable, high-impact ML products swiftly and assuredly.
Elevify advantages
Develop skills
- Production ML pipelines: design robust data, feature, and training workflows quickly.
- 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 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... 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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