Interested in Data Science? This is the Basic Math You Should Learn

Geometric Basketball Court Representing Different Maths

The great thing about data science is that there is no one specific path. You can achieve success and become involved in various ways. Just think of how many different titles exist within the field – Business Analyst, Data Architect, Data Engineer, Data Analyst…

No matter what route you take, as long as you know the essentials you are apt to become a professional. Yet every field of study starts somewhere. Here is a list of four essential math skills (in no specific order) you should focus on to fuel your data science career:

1. Applied Statistics

Applied statistics involves model formulation, model assumptions, and logistic regression. This form of math tries to explain the relationships between variables in order to demonstrate an understanding of the data. An easy way to look at applied statistics is as a way of thinking. It not only tries to pinpoint the issue at hand, it forces you to look for a pattern in the numbers. This is a great article that discusses the main objective of this branch of statistics.

2. Probability Theory

The mathematical basis for the study of random phenomena whose outcome is uncertain. Sounds like a lot, but, by pulling various data and its associated information, it can be done. In essence, you will never be able to say for a fact what the resolution will be, but you can form predictable answers. Check out this condensed introduction to probability theory.

3. Linear Algebra

This type of algebra consists of vectors, bases, functions, and matrices. Interestingly enough, linear algebra is crucial in multiple areas of modern science. By manipulating equations with large variables, you can easily solve them via any computational program. If you’re interested in machine learning, linear algebra will be useful. Read this article to find out what you can do with linear algebra.


Remember all those times you asked, “When will I use this in the real world?” Well, this is actually applicable to data science. Calculus, the mathematical study of continuous change. At its most basic level, calculus allows you to use variables and models to arrive at a solution. Anytime there is a change or a fluctuation in your analysis, the concepts learned in calculus can be applied. Here are four everyday applications calculus helps out in.

While learning these essential maths will ultimately help you build a robust set of academic skills, don’t forget to focus time on applying them through other technical mediums. KU Data Analytics Boot Camp is an immersive, in-class program that allows you to learn the fundamental skills of data analytics. Build a complete and competitive portfolio, and get started with big data. Contact our admissions team by calling (913) 956-0960 or visit our website here.

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