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Why are Data Scientists Afraid to Use Test Driven Development?
Artificial Intelligence   Data Science   Latest   Machine Learning

Why are Data Scientists Afraid to Use Test Driven Development?

Last Updated on September 2, 2024 by Editorial Team

Author(s): Lazar Gugleta

Originally published on Towards AI.

Software engineering should be one of the primary skills of Data Scientists.

This member-only story is on us. Upgrade to access all of Medium.

Programming differs from Software Engineering and especially Data Science, but the question is what connects them and what should you strive to be?

Data Science teaches us how to deal with data in a proper way but that is not enough when building bigger systems such as data pipelines or ML ops. Learning to test your software is the first step towards becoming a software engineer.

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In today’s article, I would like to present the best practices for testing your software as well as great books that will advance your skills for the duration of your whole career.

This article is not just for Data Scientists but anyone who wants to upgrade their software engineering skills.

Let’s jump right into it!

Test Driven Development is a methodology used when it comes to writing and testing code. It is a mindset in which you are writing the tests first (defining requirements) and then writing the code to fulfill those.

We cover all types of tests in this article but mostly focus on unit testing because that should be a standard. Unit testing describes tests that are run at the unit… Read the full blog for free on Medium.

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