Around once a month, I get emailed by a student of some type asking how to get into Data Science, I’ve answered it enough that I decided to write it out here so I can link people to it. So if you’re one of those students, welcome!

I’ll segment this into basic advice, which can be found quite easily if you just google ‘how to get into data science’ and advice that is less common, but advice that I’ve found very useful over the years. I’ll start with the latter, and move on to basic advice. Obviously take this with a grain of salt as all advice comes with a bit of survivorship bias.

Less Basic Advice:

1. Find a solid community

If you’re at a university, half the point of being there is to find smart, ambitious, and motivated people like yourself to learn and grow with. For my alma mater, that community was the Data Science and Informatics club. Communities/networks help you get started, keep you motivated, and are key for scoring internships and full time offers in the long term.

2. Apply Data Science to Things you Enjoy

Getting good at anything is difficult (duh), and applying data science to a field or area you care about helps you stay motivated and stand out. A couple of my examples of this are: using UF’s (alma mater) student government elections to learn about machine learning approaches, or tracking my friends’ Elo scores by recording our games of ping pong. These projects taught me essential skills without explicitly feeling like work.

Getting useful practice that is representative of the job you want to perform in the future is crucial because out of this practice you can only get one of two things:

a. The realization that you don’t actually like this type of data science in which case you should stop reading immediately

b. Valuable experience that you can easily write about (blog) or talk about (to people who want to pay you money)

This brings me to my next point.

#2020 oct opinions #career advice #data science #data scientist