As a quick anecdatum, I'm on macos and I'm definitely more than 20 years old, and there is a quite perceptible difference in responsiveness between Zed and a VSCode-based IDE for me. (Though then again I did play fast-twitched games a lot when I was younger.)
Highly recommend it as well. I'm a junior developer; that course gave me a much better sense for how to design software and answered a lot of software engineering / design-related questions that had coming up over and over again. I'm also just really allergic to handwave-y fluff, and the Mirdin stuff is just so much more concrete and precise than, e.g., the 'clean code' software engineering advice I've seen on the interwebs.
Bare minimum is basic calculus, basic linear algebra and basic statistics. By basic, I probably mean first courses for those in most undergraduate programs.
I disagree with needing none and just going along as needed. That’s how you have machine learning models that look like they work but you don’t understand why they work so there might actually be problems.
That's not quite what I said. I said to look things up if you don't understand, I made the assumption that the one asking has taken maths courses before. I interpreted bone up on as refreshing old knowledge but I could be wrong.
None, just look things up as you go along if there is something you don't understand. You're likely not going to bother understanding how the optimization functions work or how the cost functions actually work anyway. They're implementation details in most cases.
I think it depends a lot on the specific school. I'm at an Ivy League school that tries to make its classes accessible even to people without previous experience.
there are languages that have better support with dependencies though, e.g. Julia (every time I have to debug dependency issues in some other person's Python code/requirements.txt, I find myself wishing it had been written in Julia). I'm not disagreeing with the overall tenor of your post, but I do think there's a medium that's possible to strike here: maybe something like a simplified DSL in Julia, or something like https://www.visidata.org/
Another, lower-risk option: at some universities, it's quite possible for undergraduates to take graduate classes, especially if they've had the relevant background. So you could try applying to be an undergrad at such an institution. And you might not need to take that many gen ed. requirements if you find a university with flexible requirements (e.g., google 'open curriculum')
This is likely to be the easiest way to learn more theoretical math-and-CS subjects, though it'll probably be more expensive than just getting into a phd program.
I really liked all of the MIT philosophy courses[1] I've taken. Introduction to Philosophy of Language in particular was really interesting. I also took Yale's "The Science of Wellbeing"[2] after reading about it on HN. It's great, but not exactly a traditional class where you learn some piece of information and then move on. It's more like going to the gym where you're meant to continuously put what you've learned into practice. Now that I think about it perhaps I should take it again!
one example: https://about.sourcegraph.com/strange-loop/strange-loop-2019...
another: I have RSI, and while I use speech recognition, my voice gets fatigued really easily. Also, using speech recognition in public can annoy people. Real time lip reading recognition would be a serious boon for me.
