Learning data science

Undoubtedly the most complex technological field, with salaries reaching 400k for phd students and masters students reaching 200k when benefits are taken into account. These salaries are a reflection of the market, no other STEM major will see these salaries because data science is the field where the best of the best compete for these whopper salaries. It’s the intersection of high-level mathematics, statistics, and coding, that makes this field so deep. My AI professor Scott Niekum told us that ‘everyone suffers from impostor syndrome’, in other words everyone feels they need to learn more to keep up. Everyone feels like an impostor. And this is a big problem is that so many data scientists really are impostors, making real talent so desirable from top companies.

I’ve read many blog posts on data science (i have like 200 RSS feeds), and it’s really overwhelming because you have to piece things together.

This was my main motivation for not only going to get a masters, but also to pick up some statistics/data science books. Because now it’s all concentrated in one place, making it much easier to follow it like a story.

I will also be getting a certificate/minor in Applied Statistical Modeling when I graduate, because I have seen with my own eyes just how important a great mathematical foundation is to success. This means not only knowing what a dot product is, or what bayes nets are, but an intuitive understanding of the ‘why’.

I don’t know where I heard this, but someone said ‘if you are not working in data science, you are wasting your time’, because this is the field where the most REAL innovation and understanding of the world and processes happens. Why the hell would I be working as a backend engineer for some company, when deep learning companies are changing the foundations for which I would be working in. Web-development will always be in extremely high demand, AND it is very important to learn so that you can display your work to the public, but I don’t think I will work in it.

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