MLOps training
Master MLOps for building real-world churn prediction systems. Learn to deploy models with CI/CD pipelines, monitor performance, handle incidents, and ensure governance so your ML products are reliable, scalable, align with business goals, and perform well in production environments.
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 reliable churn prediction models end-to-end. Gain hands-on skills in feature engineering, model selection, evaluation, REST APIs, CI/CD pipelines, automated validation, deployment patterns, observability, incident runbooks, retraining, and governance for accurate, scalable production models.
Elevify advantages
Develop skills
- Production-ready churn modelling: build, evaluate, and explain churn models quickly.
- MLOps deployment expertise: 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: 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 workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.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 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 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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