ML Ops Course
This course equips you with essential MLOps skills to deploy, manage, and maintain machine learning models in production environments efficiently and securely.
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 dependable production swiftly and securely. You will cover canary and blue-green deployments, quick rollbacks, CI/CD for models, containerisation, Kubernetes deployment, and safe setup. The course includes experiment tracking, versioning, monitoring, drift spotting, and hands-on on-call guides to keep your ML systems steady and efficient.
Elevify advantages
Develop skills
- Production ML releases: deploy models using canary, blue-green, and quick rollback methods.
- Reproducible ML training: manage versions of data, code, and models for verifiable processes.
- Containerised ML serving: create efficient Docker images and roll out to Kubernetes securely.
- CI/CD for ML models: automate testing, security checks, and seamless deployments.
- ML monitoring & on-call: spot drift, troubleshoot issues, and maintain solid 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 switch 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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