Yes, you read that right. 99.9% of articles I come across instruct you to start with programming first. Bad move!

Data Science is a *math-laden* field, and in order to understand the many constructs in the field, you’ll need to have some kind of familiarity with math. Now, you *don’t *need a math degree for this, but you can use some of the following resources to (at least) read up on.

3 topics that are absolutely essential are Linear Algebra, Calculus, and Statistics. For the most part, you can get away with just Statistics, but either way, it’s good to know about the concepts that drive the field:

## Linear Algebra

This branch of math is used (almost) everywhere in Data Science. Your computer uses a lot of Linear Algebra in a majority of its calculations. The processing and representation of deep neural networks use Linear Algebra. Quite frankly, you’re missing out on a lot if you don’t have at least a basic understanding of the concept.

## Calculus

Like Linear Algebra, Calculus too plays a large role in Data Science. But you don’t need to be a *guru*. All you need is a basic understanding of the core principles that affect your models.