AWS Machine Learning Course
This course provides hands-on experience in building a churn prediction solution using AWS SageMaker, covering the full ML lifecycle from data preparation to deployment and monitoring.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
The AWS Machine Learning Course teaches you how to build a complete churn prediction solution using SageMaker, from selecting datasets and defining labels to feature engineering, data processing, and organising data in S3. You will learn to train and tune XGBoost models, automate pipelines, monitor drift, manage security and governance, and deploy scalable, reliable endpoints that drive measurable retention and revenue impact.
Elevify advantages
Develop skills
- Design churn ML pipelines on AWS: from raw S3 data to live SageMaker endpoints.
- Engineer high-impact churn features quickly with SageMaker Processing and Feature Store.
- Configure, train, and tune XGBoost churn models using SageMaker training jobs.
- Automate MLOps: pipelines, model registry, monitoring, and retraining on AWS.
- Secure and govern ML workloads with IAM, encryption, drift checks, and audit trails.
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 classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...

Giulio CarloDigital Marketing Student
I like how the lessons get 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 the videos are presented and transcribed, which speeds up the process!

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 CarloPrompt Engineering Student
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