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Welcome to the workshop!

Workshop
In Progress

Welcome to Feature Engineering Fundamentals in Practice!​

Today's icebreaker:​

What do these images have in common, and how does this relate to feature engineering?

Share your thoughts in the chat!

Today's agenda:​

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Review:

Recap key concepts.

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Practise:

Feature engineering for churn prediction.

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Closing:

Key takeaways and next steps.

Today's learning objectives:​

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Identify basic data quality issues

in a real-world dataset and apply appropriate data cleaning techniques to address them.

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Apply encoding techniques

to convert categorical variables into model-ready features.

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Create new features

that represent customer tenure segments, service usage levels and spend patterns to capture domain-specific insights.

✨

Evaluate the impact of engineered features

on machine learning model performance and interpretability.

Workshop slides​

Preview or download a copy of the workshop 1 slides:

Module 4 Workshop 1 — Feature Engineering Fundamentals in PracticeDownload

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In progress