Python Statistical Modeling Course
This hands-on course teaches Python-based statistical modeling for churn prediction, covering data preparation, feature engineering, model building with logistic regression and trees, evaluation, and actionable insights.

from 4 to 360h flexible workload
valid certificate 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.What our students say
As suas aulas são perfeitas. Adquiri o pacote de um ano e, finalmente, tenho a oportunidade de acompanhar diversos temas do meu interesse sem precisar mudar de plataforma... agradeço por tudo o que fazem, já recomendei vocês a outras pessoas...

Giulio CarloAluno de Marketing Digital
Eu gosto de como as lições são direto ao ponto e como eu consigo alterar capítulos e pular conteúdos que não preciso.

Mariana FerresAluna de Fotografia
Gosto do conteúdo e do modo de apresentação e transcrição de vídeos, o que acelera o processo!

Luciana AlvarengaAluna de Design de Unhas
A plataforma é rápida, simples de usar. A diversidade de conteúdo e os vídeos complementares ajudam muito no aprendizado.

Giulio CarloAluno de Engenharia de Prompt
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