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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 teaches you how to shift models from notebooks to reliable production swiftly and securely. You'll 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 processes.
  • Containerised ML serving: create efficient Docker images and deploy to Kubernetes securely.
  • CI/CD for ML models: automate tests, security checks, and zero-downtime deployments.
  • ML monitoring & on-call: spot drift, troubleshoot issues, and manage reliable models.

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.
Workload: between 4 and 360 hours

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 switch platforms... I thank you for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are 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 videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.
André Felipe
André FelipePrompt Engineering Student

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