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MLOps training

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

What will I learn?

This MLOps course teaches you to design, package, deploy, and monitor strong churn prediction models from start to finish. You will learn practical feature engineering, model selection, evaluation, building 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 modeling: build, evaluate, and explain churn models quickly.
  • MLOps deployment mastery: deploy ML models safely using CI/CD, canary, and blue-green strategies.
  • Monitoring and drift detection: monitor ML system health with metrics, logs, and alerts.
  • Model packaging and APIs: containerize models and provide 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 classes are perfect. I purchased 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 extra videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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