ML Ops Course
This course equips you with essential skills to operationalize machine learning models, ensuring reliable, scalable, and secure production deployments through modern DevOps practices tailored for ML.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
This ML Ops Course teaches you how to shift models from notebooks to dependable production swiftly and securely. You will learn about canary and blue-green deployments, quick rollbacks, CI/CD for models, containerisation, Kubernetes serving, and secure setups. The course also includes experiment tracking, versioning, monitoring, drift detection, and practical on-call runbooks to keep your ML systems stable and high-performing.
Elevify advantages
Develop skills
- Production ML deployments: deploy models using canary, blue-green, and quick rollback methods.
- Reproducible ML training: version data, code, and models for audit-ready executions.
- Containerised ML serving: create efficient Docker images and deploy to Kubernetes securely.
- CI/CD for ML models: automate testing, security checks, and zero-downtime deployments.
- ML monitoring and on-call: spot drift, troubleshoot issues, and manage 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 classes 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 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 that I don't need.

Mariana FerresPhotography Student
I like the content and the way of presentation and video transcription, 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 in learning.

André FelipePrompt Engineering Student
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