Lab Challenge

Using Python to Cleanse and Rationalize Data Challenge

Push your skills to the next level in a live environment
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Lab Steps

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Use Python to Cleanse and Rationalise Data Challenge

The hands-on lab is part of this learning path

Practical Data Science with Python
course-steps 3 certification 4 lab-steps 3
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Difficulty

Beginner

Time Limit

2h 30m

Students

13

Ratings
5/5
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About Lab Challenges

Lab challenges are hands-on labs with the gloves off. You jump into an auto-provisioned cloud environment and are given a goal to accomplish. No instructions, no hints. To pass, you'll have a limited time to demonstrate your problem-solving skills and get the checks that inspect the state of your lab environment.

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Challenge Description

Data cleansing is an important task that every data scientist should be comfortable performing. You will put your basic knowledge of Python to work in this lab challenge in order to perform a simple form of data cleansing on text.

In this lab challenge, you will be provided with a web browser-based integrated development environment (IDE) with an incomplete code file pre-loaded. The challenge mission and code file both describe what you must do to complete the challenge before time runs out. This is a real environment, which means you can prove your knowledge in an applied situation, leaving behind multiple choice questions for a dynamic performance-based exam situation.

What will be assessed

  • Python functions
  • String operations
  • User-defined functions

Intended audience

  • Budding data scientists
  • Python beginners

Prerequisites

  • Completion of the Practical Data Science with Python learning path is recommended
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About the Author

Delivering training and developing courseware for multiple aspects across Data Science curriculum, constantly updating and adapting to new trends and methods.