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MLOps training

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

What will I learn?

This MLOps course teaches you to design, package, deploy, and monitor reliable churn prediction models end-to-end. Gain hands-on skills in feature engineering, model selection, evaluation, building REST APIs, CI/CD pipelines, and automated validation. Master deployment strategies, observability tools, incident response plans, retraining methods, and governance practices to ensure models remain accurate, scalable, and ready for production environments.

Elevify advantages

Develop skills

  • Develop production-ready churn models: build, evaluate, and interpret them efficiently.
  • Achieve MLOps deployment expertise: deploy ML models securely using CI/CD, canary releases, and blue-green strategies.
  • Implement monitoring and drift detection: monitor model performance with metrics, logs, and alerts.
  • Package models and create APIs: containerise models and deliver predictions through REST endpoints.
  • Create incident response playbooks: manage rollbacks, outages, and performance issues effectively.

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 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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