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Customer Analytics: Preparing Data for Modeling

Apply your knowledge of data types and categorical data to prepare a big dataset for modeling!

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1 Tasks1,500 XP

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Project Description

Being able to create predictive models is very cool, but translating fancy models into real business value is a major challenge if the training data isn't stored efficiently.

You've been hired by a major online data science training provider to store their data much more efficiently, so they can create a model that predicts if course enrollees are looking for a job. You'll convert data types, create ordered categories, and filter ordered categorical data so the data is ready for modeling.

Project Tasks

  1. 1
    Convert the data types of each column to store the data more efficiently.

Technologies

Python Python

Topics

Data Manipulation
James Chapman HeadshotJames Chapman

Curriculum Manager, DataCamp

James is a Curriculum Manager at DataCamp, where he collaborates with experts from industry and academia to create courses on AI, data science, and analytics. He has led nine DataCamp courses on diverse topics in Python, R, AI developer tooling, and Google Sheets. He has a Master's degree in Physics and Astronomy from Durham University, where he specialized in high-redshift quasar detection. In his spare time, he enjoys restoring retro toys and electronics.

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