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Predictive Modeling Course

Predictive Modeling Course
flexible workload of 4 to 360h
valid certificate in your country

What will I learn?

This Predictive Modelling Course offers a complete, practical process for predicting customer spending accurately using monthly data. Learners will set precise targets, avoid data leaks, perform detailed exploratory checks, build strong time-based and behaviour features, and choose, train, validate linear and tree models with time splits, key business measures, and clear outputs ready for marketing use.

Elevify advantages

Develop skills

  • Data preparation for spend prediction: clean, encode, and create effective features.
  • Strong model training: choose, fine-tune, and combine linear and tree-based models.
  • Time-sensitive validation: create safe splits, cross-validation, and stability tests.
  • Error and ROI assessment: connect MAE, lift, and calibration to revenue impact.
  • Model explanation: use SHAP to clarify limits and actions for business teams.

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 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 that I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way of presentation and video transcription, 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 in learning.
André Felipe
André FelipePrompt Engineering Student

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