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A Potential Data Science Foundation for Math Backgrounds

A course guide to help you get started with Data Science

John DeJesus
Photo by Mirko Blicke on Unsplash

You decided to join the data science field! Congrats! But maybe you aren’t sure what you want to do in the field yet but you want to get in there yesterday. Many advocate that you should dive into a project of your own to learn what you need. Although this is a good approach you will learn a lot from, you may not be comfortable with this because of a lack of coding background. You may just prefer going through a few courses first to build a foundation for tackling projects.

That is ok. So let me help you out.

Photo by Erik Mclean on Unsplash

As someone with a math background (master’s in pure mathematics), this was my issue. I wanted to get into the field but didn’t have enough coding skills outside of a random JavaScript class I took many years ago. I also didn’t know which aspect of data science I liked since the field hadn’t made distinguishing titles for each of the subfields yet.

Here I will give you my opinion on what courses you could select for a foundation and why. This selection is based on my experience trying to get into the field coupled with my experience as a data scientist now. This could be a useful selection if you still aren’t sure which part of the data science field you want to dive into. I will also provide the exact classes I took following this format at the end of the explanations. If you simply want to see a quick list without explanations, simply look below:

  1. A Python or R programming course.
  2. A SQL course.
  3. A data manipulation/visualization course.
  4. A machine learning course.
  5. A deep learning course.

Now for the explanations!