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Predictive Analytics Models Course

Predictive Analytics Models Course
4 to 360 hours of flexible workload
certificate valid in your country

What Will I Learn?

The Predictive Analytics Models Course teaches you how to build, evaluate, and deploy churn prediction models that deliver tangible outcomes. You will learn data ingestion, feature engineering, model selection, and probability calibration, then convert outputs into straightforward reports, prioritised action plans, targeted campaigns, and A/B tests with KPIs, ensuring robust, explainable, and scalable customer retention strategies.

Elevify Advantages

Develop Skills

  • Build churn models: design, train, and tune predictive models quickly.
  • Engineer RFM and behavioural features: transform raw customer data into meaningful signals.
  • Evaluate models with business KPIs: connect metrics to actual revenue impact.
  • Explain model insights: translate churn drivers into clear action plans.
  • Plan and test interventions: design A/B campaigns to reduce churn swiftly.

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 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 Carlo
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 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 supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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