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MLOps training

MLOps training
flexible workload of 4 to 360h
valid certificate in your country

What will I learn?

This MLOps Training teaches you to design, package, deploy, and monitor strong churn prediction models from start to finish. You will learn practical feature engineering, model selection, and evaluation, then create reliable REST APIs, CI/CD pipelines, and automated validation. Gain expertise in deployment patterns, observability, incident runbooks, retraining strategies, and governance to keep models accurate, scalable, and ready for production.

Elevify advantages

Develop skills

  • Production-ready churn modelling: build, evaluate, and explain churn models quickly.
  • MLOps deployment skills: deploy ML models using CI/CD, canary releases, and blue-green strategies safely.
  • Monitoring and drift detection: monitor ML system health with metrics, logs, and alerts.
  • Model packaging and APIs: containerise models and deliver predictions through REST APIs.
  • Incident response playbooks: manage rollbacks, outages, and performance issues effectively.

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 lessons 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 Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change 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 help a lot with learning.
André Felipe
André FelipePrompt Engineering Student

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