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Skills application

Instruction and application
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Predicting customer churn

In this skills application, you will apply your knowledge of variable characterisation, transformation techniques and feature selection by designing an end-to-end workflow for a churn prediction problem.

The goal is to choose transformations that reveal the strongest signals while balancing interpretability, noise reduction and model performance.

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Success criteria

To successfully complete this activity, write a report of up to 1,800 words that explains:

  • What the key drivers behind churn are
  • What features you engineered to reveal those insights
  • How you can be confident in the quality of those insights
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Stakeholder challenge

A stakeholder has noticed that a model trained on the raw data appears to produce higher accuracy. Part of your task is to explain why a model built on engineered features may still be the better business solution.

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Instructions

Launch the Skillable lab and work through techniques for engineering new features. At the end of the lab, you will build a model using engineered features to predict customer churn.

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Important access information

Please set aside 30 uninterrupted minutes before opening the lab. Your attempt expires after 30 minutes, and you are limited to a maximum of five attempts within 90 days from your initial attempt.