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ML Ops Course

ML Ops Course
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.
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... I appreciate everything you do, I've already recommended you to others...
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 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 supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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