To come back to modelling: I see daily people with a cursory understanding of models misusing their tools and not noticing blatant problems. Just today:
- someone using random forest to predict a quantity (which you can do, it’s often nicknamed “random tree regression”) so the first thing their did was to turn quantities to predict to as many categorical variables;
- someone else, on the same problem didn’t see why having a massively higher mean square error on the out-of-bag sample compared to the test sample was suspicious.
I’m not saying that five years of university will solve that, but I’m noticed that taking the time to dig into the model, vs. assuming it’s like a car -- you only need to turn the key and go with it -- is strongly correlated with making those mistakes.
I'm a front-end dev (amonst other things), so I'm pretty comfortable with React, Angular, etc. And therr are definitely cases where they make sense. But simple static or server side rendered sites are much simpler now.
There are three different roles that I think you are conflating: Designing, Building (and maintaining), and using.
Each has a different skillset. But to think that you need to determine the convergence of models makes no sense to me. Why can't an undergrad build a simple classifier?
And in finance, CAPM uses regression. Every single finance undergrad in the country learns it. Are you implying that they can't because they don't know how the model will converge with something else?
Seriously, it really frustrates me when people look down on undergrads and say "Oh, they can't do it". Baloney. I've met tons of really smart, focused undergrads. And some pretty f-ing stupid grad students (at a PhD level to boot!).
Two decades ago, you needed some pretty heavy CS to build a web page. Today, my mom can do it. With your line of thinking, that wouldn't be possible.