>Secondly, for some reason data science just doesn't excite me as much as typical software development goes
Fair enough. Part of the reason is "data science" has been so jammed pack of nonsense and people who don't do the actual work of building things, as you describe below.
> What i do particularly enjoy is good ol' back end web development. I don't have a degree in computer science but working on a information system degree with focus on "programming", I dream/working my ass to become cult of "software engineer" type II, a sophisticated software developer/programmer. I love building layers, optimizing code, learning new tools, algorithms data structure (without knowing math), creating unit tests, following programming paradigm. It excites me so much. And my core skills to dive into is block chain..
Ok this makes sense. But I'd be worried about 5 years from now. When all the little gears and things that go on in backend becomes a commodity (or abstracted away in the "cloud"), what are you going to do?
> I love studying that topic too and all the algorithms it comes with it.
That spark of interest in the algorithms, (which is just about logic, which is what math is basically about in the end), is basically the essence of what makes "Data science" so attractive.
"But I'd be worried about 5 years from now. When all the little gears and things that go on in backend becomes a commodity (or abstracted away in the "cloud"), what are you going to do?"
Well, over the last 8 years or so I started out in a similar kind of place, and have gotten quite good at building CRUD and business logic and glue, and fixing crap on the front end, and configuring servers.
Maybe I can stand in for the OP a few years down the line?
Over the last quarter, I've been splitting my time between things like linux admin automation and a set of pre-calculus core classes.
To answer your question on my personal scale, my whole ability to do this kind of work with my mediocre CS education (my BA is in Philosophy, and my PhD work is in Lit) is premised on leveraging the points in the systems where "all the little gears and things that go on in backend have [become] a commodity"... hence I just integrate ERP systems with WordPress or try and clean up some business's AWS drupal hosting setup some crap like that. That's been a fun and rewarding conjunction of my love for systems and the commodification of parts of IT/ programming work.
My hope is that by the time all the little bits of these data science topics become "abstracted away" over the next couple of years, I will understand the general underlying things well enough to use them. But who knows if that is a good bet or not... certainly not me.
However, it feels perfectly fine to learn things like math... I'm way, way better at it than I was as an undergrad 20 years ago and so it's quite a lot more fun for me. It's not like knowing some math has no application outside of this narrow field.
I dunno if my personal answer (keep learning, and enjoy fixing crap) matches the OP or helps extend your points/ question, but I've been getting a lot of fun (and some money) out of following my answer.
>Secondly, for some reason data science just doesn't excite me as much as typical software development goes
Fair enough. Part of the reason is "data science" has been so jammed pack of nonsense and people who don't do the actual work of building things, as you describe below.
> What i do particularly enjoy is good ol' back end web development. I don't have a degree in computer science but working on a information system degree with focus on "programming", I dream/working my ass to become cult of "software engineer" type II, a sophisticated software developer/programmer. I love building layers, optimizing code, learning new tools, algorithms data structure (without knowing math), creating unit tests, following programming paradigm. It excites me so much. And my core skills to dive into is block chain..
Ok this makes sense. But I'd be worried about 5 years from now. When all the little gears and things that go on in backend becomes a commodity (or abstracted away in the "cloud"), what are you going to do?
> I love studying that topic too and all the algorithms it comes with it.
That spark of interest in the algorithms, (which is just about logic, which is what math is basically about in the end), is basically the essence of what makes "Data science" so attractive.