Map of Computer Science






The field of computer science summarised. Learn more at this video’s sponsor https://brilliant.org/dos

Computer science is the subject that studies what computers can do and investigates the best ways you can solve the problems of the world with them. It is a huge field overlapping pure mathematics, engineering and many other scientific disciplines. In this video I summarise as much of the subject as I can and show how the areas are related to each other.

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A couple of notes on this video:
1. Some people have commented that I should have included computer security alongside hacking, and I completely agree, that was an oversight on my part. Apologies to all the computer security professionals, and thanks for all the hard work!
2. I also failed to mention interpreters alongside compilers in the complier section. Again, I’m kicking myself because of course this is an important concept for people to hear about. Also the layers of languages being compiled to other languages is overly convoluted, in practice it is more simple than this. I guess I should have picked one simple example.
3. NP-complete problems are possible to solve, they just become very difficult to solve very quickly as they get bigger. When I said NP-complete and then “impossible to solve”, I meant that the large NP-complete problems that industry is interested in solving were thought to be practically impossible to solve.

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26 thought on “Map of Computer Science”

  1. Hey thanks for all the comments! Yes I agree that I should have added in computer security alongside hacking. It is a huge and important field so I regret leaving it off. And I should also have mentioned interpreters along with compilers as this is an important concept, especially having coded a fair amount of python I have no excuses. I added a couple of notes in the video description.

    Thanks for pointing these omissions out, and thanks for all the words of encouragement as well. I was trying something new with the graphic design on this one, trying to match the look to the subject matter and I think it worked out well.

  2. I mean. Are we not all computers right now? We do compute. Which also makes the claim you made that "a smart phone has more computing power than the sum of all computing power world wide back in 1960s" a bit questionable.

  3. hello nice guy.
    i've attacked by hacker who i've known they're chinese in France paris.they builder one website calls HUARENJIE.com
    and control my computer now. how should i do now? even my smartphone is attacked by them.i can't even send my message. please help me.thank you very much.
    could you please contact me by my email: [email protected]live.cn

  4. That moment when you feel like a badass because you knew a little something about every topic he mentioned 😀

    Great video and great map! Thank you

  5. You mentioned the formal method twice. It's good though. And mention SAT, but miss SMT. Also, you had forgotten the whole Symbolic AI field, also program languages theory and type theory.

  6. 1:55 while that's an interesting problem, imo you should relativize the utility of this result: The halting problem asks if a program runs for ever or or if it takes finite time. In practice, we don't only have finite time; we have strongly bounded time. The halting problem says nothing about that. There is no real use of this result in practice.

  7. Quantum Computers are equivalent to Turing Machines in terms of computability. Your comment at 1:06 (except from a quantum computer) is not correct. They solve the same set of problems, the difference is that their efficiency profile is radically different from today's computer, which puts some problems within reach that weren't there before _in practice_, but the Quantum Turing Machine is equivalent to general TM's.

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