ML Ops Course
This course equips learners with essential MLOps skills to deploy, monitor, and maintain machine learning models in production environments, ensuring reliability, security, and efficiency.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This ML Ops Course teaches you how to deploy models from notebooks to reliable production swiftly and securely. You will cover canary and blue-green releases, quick rollback, CI/CD for models, containerisation, Kubernetes serving, and secure setup. The course includes experiment tracking, versioning, monitoring, drift detection, and practical on-call runbooks to keep your ML systems stable and performing well.
Elevify advantages
Develop skills
- Production ML releases: deploy models using canary, blue-green, and quick rollback.
- Reproducible ML training: version data, code, and models for audit-ready runs.
- Containerised ML serving: build efficient Docker images and deploy to Kubernetes securely.
- CI/CD for ML models: automate tests, security scans, and zero-downtime rollouts.
- ML monitoring & on-call: detect drift, debug incidents, and run reliable churn models.
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 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 thank you 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 really help with learning.

André FelipePrompt Engineering Student
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