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Python Statistical Modeling Course

Python Statistical Modeling Course
from 4 to 360h flexible workload
certificate valid in your country

What will I learn?

Master churn-focused statistical modeling with Python in this concise, hands-on course. You will load and profile data with pandas, clean and engineer powerful features, and run exploratory analysis to uncover key churn drivers. Then you will build and interpret logistic regression and tree-based models, evaluate performance, and turn results into clear reports, A/B tests, and deployment-ready, ethical recommendations that drive measurable impact.

Elevify advantages

Develop skills

  • Build clean churn datasets: load, profile, and fix data fast with pandas.
  • Engineer powerful churn features: sessions, cohorts, recency, and engagement.
  • Fit and explain logistic models: Python pipelines, AUC, and clear odds ratios.
  • Compare and tune models: tree ensembles, SHAP insights, and robust validation.
  • Turn stats into action: A/B tests, dashboards, and concrete churn playbooks.

Suggested summary

Before starting, you can change the chapters and 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... I appreciate 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 extra videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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