Predictive Modeling Course
This course teaches a complete workflow for building predictive models to forecast customer spend, covering data preparation, feature engineering, model selection, validation, evaluation, and communication of results for marketing applications.
4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Predictive Modelling Course provides a practical, end-to-end workflow for accurate spend prediction on customer-month data. You will define clear prediction targets, prevent data leakage, conduct thorough exploratory analysis, engineer robust temporal and behavioural features, and select, train, and validate linear and tree-based models with time-aware splits, business-focused metrics, and interpretable, deployment-ready outputs for marketing decisions.
Elevify advantages
Develop skills
- Data prep for spend prediction: clean, encode, and engineer high-signal features.
- Robust model training: select, tune, and ensemble linear and tree-based models.
- Time-aware validation: design leakage-safe splits, CV, and stability checks.
- Error and ROI evaluation: link MAE, lift, and calibration directly to revenue.
- Model storytelling: explain SHAP, limits, and next steps to nontechnical stakeholders.
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.What our students say
Your lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to change platforms... I'm grateful 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
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Luciana AlvarengaNail Design Student
The platform is fast and simple to use. The diversity of content and complementary videos really help with learning.
André FelipePrompt Engineering Student
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