Decision Tree Course
Master decision trees, Random Forests, and Gradient Boosted Trees to predict customer churn accurately. Gain skills in data preparation, model tuning for imbalanced data, explainability with SHAP and LIME, and converting insights into revenue-boosting retention plans and experiments.
4 to 360h flexible workload
certificate valid in your country
What will I learn?
This course teaches building precise churn prediction models from customer data. Learn data prep, feature engineering, tree-based models like Decision Trees, Random Forests, and Gradient Boosted Trees, plus SHAP for explanations and actionable retention strategies.
Elevify advantages
Develop skills
- Prepare churn data: clean, profile, and engineer features efficiently.
- Build tree ensembles: create, tune, and evaluate Decision Trees, Random Forests, and boosted models.
- Handle imbalanced data: use cross-validation, stratification, and class weights.
- Explain models: apply SHAP, LIME, and feature importance for insights.
- Generate actions: transform churn findings into retention strategies and tests.
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
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