Decision Tree Analysis Course
This course equips learners with practical skills to build, tune, and apply decision tree models for data-driven decision-making, focusing on interpretability and business impact.

4 to 360h flexible workload
certificate valid in your country
What will I learn?
This Decision Tree Analysis Course shows you how to define a clear high-cost target, build transparent trees in Python or R, and tune key hyperparameters for reliable performance. You will handle missing data, class imbalance, and outliers, evaluate models with ROC, F1, and calibration tools, and communicate results, risk segmentation, and business-ready recommendations to non-technical stakeholders with confidence.
Elevify advantages
Develop skills
- Decision tree modelling: build interpretable CART models fast in R and Python.
- Performance tuning: optimize depth, pruning, and class weights for sharp metrics.
- Cost-sensitive evaluation: set thresholds using AUC, F1, and business impact.
- Transparent preprocessing: clean, encode, and engineer features for clear trees.
- Stakeholder reporting: turn tree outputs into concise pricing and risk insights.
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 are saying
Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to switch platforms... I thank you 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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The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.

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