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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

<p>Being able to create predictive models is <em>very</em> cool, but translating fancy models into real business value is a major challenge if the training data isn&#39;t stored efficiently.</p> <p>You&#39;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&#39;ll convert data types, created ordered categories, and filter ordered categorical data so the data is ready for modeling.</p>

Project Tasks

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

Technologies

Python Python

Topics

Data ManipulationImporting & Cleaning Data
James Chapman Headshot

James Chapman

Curriculum Manager, DataCamp

James is a Curriculum Manager at DataCamp. He has a Master's degree in Physics and Astronomy from Durham University, where he specialized in quasar detection and tutored Math and English. He joined DataCamp as a learner in 2018, and the data skills learned on DataCamp were quickly integrated into his scientific projects. In his spare time, he enjoys restoring retro toys and electronics.

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