Clean a Churn Dataset Before Training

Fix real data-quality problems in a churn dataset before any model can trust it.

A beginner AI Engineering challenge worth 3 points. Solve it hands-on in a real AI Engineering environment in your browser - no local setup, no fake shells.

The Challenge

Scenario: A churn-prediction dataset has mixed numeric/text values, missing income and age, blanket zero-filling standing in for "unknown", and an exit-survey field that leaks the cancellation outcome directly into the training data.

Coerce invalid values to proper numeric types, median-impute the real missing values, drop the leaking column, and keep every row aligned with its target label. Run check.