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Customer Analytics: Preparing Data for Modeling

IntermediateSkill Level
4.8+
1,726 reviews
Updated 05/2025
Apply your knowledge of data types and categorical data to prepare a big dataset for modeling!
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Included withPremium or Teams

PythonData Manipulation
1 hr
1 Task
1,500 XP
17,019

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Project Description

Customer Analytics: Preparing Data for Modeling

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.

Customer Analytics: Preparing Data for Modeling

Apply your knowledge of data types and categorical data to prepare a big dataset for modeling!
Start Project
  • 1

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

Don’t just take our word for it

*4.8
from 1,726 reviews
84%
16%
0%
0%
0%
  • Jorge
    3 minutes ago

  • Shubham
    8 hours ago

    This was a great project covering the previous lessons.

  • Sikhalo
    16 hours ago

    This was a fun little project it really helped me focus my data preparation skills

  • Oluwafunmilayo
    16 hours ago

  • Klyde Adam
    2 days ago

  • Luan
    2 days ago

Jorge

"This was a great project covering the previous lessons."

Shubham

"This was a fun little project it really helped me focus my data preparation skills"

Sikhalo

FAQs

Is this project suitable for beginners?

Yes! This project is suitable for beginners. You can apply your basic knowledge of data types and categorical data to complete the tasks.

What is the programming language of this project?

The programming language of this project is Python.

Can I add this project to my Data Portfolio?

Yes, you can add this project to your data portfolio after completion!

Do I need to download any software to complete this project?

No, you will not need to download any additional software as the full project can be completed using DataCamp Workspace.

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