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ML Ops Course

ML Ops Course
from 4 to 360h flexible workload
valid certificate in your country

What will I learn?

This ML Ops Course shows you how to move models from notebooks to reliable production quickly and safely. You will learn canary and blue-green releases, fast rollback, CI/CD for models, containerization, Kubernetes serving, and secure configuration. The course also covers experiment tracking, versioning, monitoring, drift detection, and practical on-call runbooks so your ML systems stay stable and high performing.

Elevify advantages

Develop skills

  • Production ML releases: ship models with canary, blue-green, and fast rollback.
  • Reproducible ML training: version data, code, and models for audit-ready runs.
  • Containerized ML serving: build lean Docker images and deploy to Kubernetes safely.
  • 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.
Workload: between 4 and 360 hours

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 Carlo
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 Ferres
Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
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 Carlo
Giulio CarloPrompt Engineering Student

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