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Anonymous at Wed, 10 Apr 2024 19:23:18 UTC No. 16122869
Map original came from a youtube video where the uploader was mentioning the scam that is STEM degree's,
I want to get into AI and currently don't have the funds to just jump into college or university to get a degree yet (will work and save up but don't think I should wait until then to learn).
So I copied the list down and made a rudimentary road map and now I'm seeking two things;
1.) Any CS Major or Graduate, what or how would you modify this map?
2.) Most importantly, I am seeking good college text books that covers these blocks of learning
Anonymous at Wed, 10 Apr 2024 19:29:41 UTC No. 16122885
It would be easier to help you if you mentioned what you already know, uni curriculums have a lot of bloat. And the first filter will be whether you can keep motivated to program regularly when you don't have a class forcing you to do that. A lot of people think programming is boring and that's ok, don't force yourself into doing something you hate just because the field is hyped right now, nobody needs more pajeets. And if you just want a good paying job you don't need to do something that requires knowledge of a million different things like AI.
Anonymous at Wed, 10 Apr 2024 19:32:01 UTC No. 16122888
>>16122885
>It would be easier to help you if you mentioned what you already know
Just for the sake of making things easier,
Lets assume I know up until Pre-Cal 1 and Intro to Comp Sci (I have enough knowledge to enter these two learning blocks but have not yet)
So based upon that, what answers can you provide for;
>2.) Most importantly, I am seeking good college text books that covers these blocks of learning
Anonymous at Wed, 10 Apr 2024 19:40:51 UTC No. 16122902
>>16122888
>C A Modern approach by KN King
C is the mother of high level programming languages and will force you to actually understand how things work. It's also not hard like some people say it is, them saying that goes to show how stupid people have flooded CS. And once you run into issues like struggling to manage memory you'll learn more about other subfields and maybe come to appreciate different languages. You need a language of choice to start practicing data structures and C is a great introductory choice. After you've done that book you can get Algorithms by CLRS and start trying to implement those (and expect to fail often, that's what will truly teach you). As you try to make things work you'll learn about other things you need to learn.
>Structured Computer Organization by Tanenbaum
How computers work, important to be able to study operating systems and networks later (for which C will also be extremely useful). Want to write a program that allows you to send something to another computer? You'll need to understand these to do it right. Tanenbaum himself has books on OSs and networks for later. If you like computer architecture you can also go with Computer Architecture and Design by Patterson and Hennessy.
Those will already keep you busy at first so there's no reason to dump a huge list of other topics. Something like theory of computation by Sipser would be overkill if you don't have the basics down (memorizing stuff you won't practice only to forget it later is a waste of time).
Eventually you can check Norvig and Russell's AI book but honestly you'll simply regurgitate concepts if you're not able to do other CS stuff first. And if you want to dive deeper into stuff like data science and machine learning you'll need to study some statistics, at least to understand how some libraries work. But like I said go look up stuff in the wiki, no point in dumping names here.
Anonymous at Wed, 10 Apr 2024 19:43:31 UTC No. 16122914
>>16122902
Much appreciation Anon! I sincerely thank you for this.
Anonymous at Thu, 11 Apr 2024 04:24:44 UTC No. 16123591
>>16122869
sharing an update to my OP, just in case anyone else is interested in the same thing.
I have not been able to verify or compare these titles to see if they are the best to use for these subjects, but this is a start.
Anonymous at Thu, 11 Apr 2024 05:15:52 UTC No. 16123634
>>16122869
The /sci/ wiki is really helpful for that. Don't skip the mathematical prerequisites, you'll regret it later on. For linear algebra, I've read Katznelson's terse introduction into linear algebra which covers a lot in just 200 pages, for analysis I read Zorich's books as they're more focused on applied math.
Anonymous at Thu, 11 Apr 2024 05:56:04 UTC No. 16123655
>>16122869
Serge Lang. Algebra