What learning path/discipline in data science I should focus on?

The tl;dr: “Data science” is a broad field including many different specializations; which particular sub-role do you find most appealing? Statistics, machine learning, software engineering, data visualization…?

Hm, how can I say this … it’s a pity that our day only has 24 hours, and there is only so much that we can learn as an individual person. So, I think it is somewhat important to reflect on your goals and your interest when you are picking your study topics. Although it has a “bad ring” to it, the phrase “being a jack of all trades” is certainly very tempting and useful if you work as an individual. As a “data scientist” there are endless topics you can get lost in, from programming to statistics, databases, differential calculus, … Of course, it’s useful to know a bit of everything, but I think it is impossible to become a master in everything in a given amount of time. For example, data scientists rarely work on their own but are often part of bigger teams with different areas of responsibilities. Some people are really good at stats; some people are responsible for building the framework to collect, clean, and extract data. Some people develop new algorithms, and some are “data scientist-programmers” who focus on implementing them most efficiently. For example, I’d say that I am a pretty good Python programmer, but my Java skills are really rudimentary. I think a better knowledge of Java would help me here and there, but my focus is more on the Machine Learning part; Python is already sufficient for me to implement all my ideas. So rather than investing in learning a brand new programming language, I try to focus more on my strength, e.g., picking up fresh ML concepts and staying on top with the current developments in the field. Of course, I’d like to learn a new programming language since it could be useful, but I also know that I only have so much time to learn all these things … ;)

What I am trying to say is that it is probably not a bad idea to think about where you want to be in xx years, and what does it take to get there. Which are the things and skills that are necessary to get you there? I would focus on these first!