Ask HN: How to improve data science skills as a software dev?
Hey HN, I&#x27;m a software engineer wanting to become good in data science. I&#x27;m already good enough at the math I think - linear algebra, analysis, diff eqs, probability, etc.  - aren&#x27;t a problem. I know theoretically it should be easy, heck I know how to build software and I&#x27;m pretty darn good at maths.<p>The problem is every time I try to start learning data science I use the same approach I do for software dev and it doesn&#x27;t seem to carry over.<p>For instance, if I want to learn about something new in the software world say about random number generators, I&#x27;ll go look at how one&#x27;s built in some language and then build my own (or vice versa), learning concepts I need to as I go. Or I can also just build things I need like cli tools, parsers, rest clients, etc. in the new framework&#x2F;language so I don&#x27;t feel like I&#x27;m wasting my time because I can use these in my work.<p>With data science it seems like most &quot;learning projects&quot; I can think of and which are applicable in my work boil down to just data wrangling and simple regressions, which after you&#x27;ve done a couple really don&#x27;t teach you anything new.<p>How can I find data science projects that are more complicated (and ideally still applicable)?<p>Also, I&#x27;d really be interested to know what the &quot;core&quot; concepts a data scientist has to know are, not math skills or tooling, just the rest :) ?<p>I&#x27;ve also been thinking about offering to do data science work to anyone for free just to get exposure to more complicated problems. Ideally, I could find a real data scientist who could just shove stuff my way and whom I could learn from. Does this make sense?<p>Any links or advice greatly appreciated. Thanks in advance!