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Does anyone have a similar resource for applied math? I am looking for something that goes beyond the standard calculus, linear algebra and stats material. For example, optimization, numerical analysis, stochastic processes, dynamical systems etc.
Does anyone have a similar resource for applied math? I am looking for something that goes beyond the standard calculus, linear algebra and stats material. For example, optimization, numerical analysis, stochastic processes, dynamical systems etc.
I take it you've done Discrete Mathematics and have enjoyed it? If you haven't, I highly recommend going that direction first, as imho it is the most beneficial math class a programmer can take in college.
This is a bit hypocritical coming from a self-taught dropout, but I have kind of grown to dislike a lot of these "learn programming on your own!" things/bootcamps/courses. This isn't because of some idea that it's bad to learn programming for fun, but more that I think it's kind of reductive to try and squeeze things down to a streamlined lesson to begin with...There's a reason college takes four or more years; it ta…
Does anyone have a similar resource for applied math? I am looking for something that goes beyond the standard calculus, linear algebra and stats material. For example, optimization, numerical analysis, stochastic processes, dynamical systems etc.
The first thing that came to mind (maybe due to mentioning stochastic) is MITx's https://micromasters.mit.edu/ds/ Masters in Data Science. It's statistics, but 102. (Of the alternative MIT 6.0002, which is MIT's intro to DS stat class.) I take it you've done Discrete Mathematics and have enjoyed it? If you haven't, I highly recommend going that direction first, as imho it is the most beneficial math class a programme…
Thanks for the link! Though it looks too basic for me, I was hoping for something on the more advanced topics I mentioned.
Maybe the problem is that it's pretty hard to gauge how good education of any kind is. We have countries all over the globe doing things a bit differently, and we have public and private schools with different methodologies. But, while I personally don't have the answers, and obviously our governments probably aren't sure either, clearly there is work being done in figuring out what works and what doesn't.
What are some good resources for identifying the best forms of education?
Are there any resources for identifying the best way(s) to learn computer science, or entry-level computer programming, or foundational software engineering?
I really like this list, but believe it's wrongly titled. I'm a nuclear engineer, who pretty much just writes modelling software all day. The software architecture stuff is something I've never been taught and always felt would be immensely valuable to learn. Some good resources for that on this list. Also a request for any resources of scientists trying to get their head around how to write good software, we're all…
I guess this is hard to find, because theres no generic way that will work for all programming languages and contexts.
But i will tell you where i often find them: directly in source code.
People that are really good at this, dont have time to teach, and if they teach, its hard to get to the point to teach the 'tricks' implemented directly in source code.
Also, im my experience, besides the generic algorithms and protocols that you can implement in any language, the rest is very much context dependent.
So in the context of C++, that you have mentioned, there are for instance, at least, two great C++ shops for great source code, experience and tricks that i particularly like: Google and Microsoft C++ stuff.
The problem with this approach, is that you have to be like a 'source code vulture', opening up the engines you are interested in, and willing to expend some time reading and understanding what the source code do.
With this you can match and map with the more abstract knowledge in the field.
I've learned A LOT reading others people source code, specially the 'canonical' pieces of software out there.
Something no book wandering over abstract ideas can taught you about (the first exception to this that comes to mind is Tanenbaum books about OS, but he made Minix as a source code realization of the ideas in the book, so...)
I guess I’m not the target audience, which is fine
why doesnt this exist for any other field? you never hear of a DIY mathematician or economist...further proves that tech is a trade not a profession
Everyone is a professional these days.
Earlier quoted context omitted.
> College CS courses aren't necessarily designed to be practical; many are more theoretical and not really practical for day-to-day SWE jobs. This is the mentality that I really dislike about these courses. How exactly do you get to decide if something is just "theoretical" and "not really practical"? Everything in CS was purely theoretical at one point. It's easy to say "practical means stuff that is used in the ind…
I guess my question is if there's even such a thing as a "non self taught front end developer"? No 4 year university will teach you React as part of a CS degree. Most probably won't even teach JavaScript. Point is, becoming a good developer is largely a self-taught discipline as is.
DISCLAIMER: I'm not a frontend developer.
They will teach you why React is used though, at least indirectly. A good professor will explain the virtues and drawbacks of immutability, and explain how it affects performance; with this understanding, it will help you choose whether or not React or another framework is more appropriate.
> Point is, becoming a good developer is largely a self-taught discipline as is.
It can be, but to write code that ends up performing well, you typically have to have some underlying understanding of the "guts" of the libraries you're using.
Dumb example, to find the smallest element of a list, I used to sort the list, and grab the first element out of it. This will work, but if I had taken any data structures or algorithms class, I would have learned that this is an O(n log n) process, whereas finding the min only requires O(n). This won't matter for smaller lists, but for something big it absolutely will.
Now, maybe I'm just dumb, I'm willing to accept that, but it's not like when I realized this later and changed to the faster version, that the code for finding the min was appreciably shorter or prettier or easier to maintain, it was only faster.