Marketing Analytics: Predicting Customer Churn in Python
4.8(167) on DataCamp
Intermediate 4 hours English Course Certificate
Our recommendation
A DataCamp course walking through the full churn-modelling workflow on the real Telco Churn dataset — exploratory analysis, preprocessing, feature engineering and modelling. Hands-on and practical, it is a strong applied project for people who know some Python and want a real marketing-analytics use case.
Good for: An applied, end-to-end customer-churn modelling project.
Less suitable if: You lack Python/ML basics or want theory.
Marketing Analytics: Predicting Customer Churn in Python walks through the full churn-modeling workflow on the real Telco Churn Dataset: exploratory analysis and visualization, preprocessing (encoding, scaling, feature engineering), building scikit-learn classification models, evaluating them with accuracy, precision, recall, ROC-AUC and F1, and finally tuning hyperparameters to understand what actually drives churn.
What you'll learn
Explore and visualize churn data with pandas and Seaborn
Evaluate models with accuracy, precision, recall, ROC-AUC, and F1
Tune hyperparameters and interpret feature importances
Communicate churn drivers as actionable insights to stakeholders
This course includes
4h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
DataCamp runs on a subscription — roughly $14/month billed annually (more month-to-month), with the first chapter of each course free to try. A certificate of completion is included with the subscription.
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DADataCamp4.8(167)
Marketing Analytics: Predicting Customer Churn in Python