I'd like to take this opportunity to explain the biggest problem with almost all code learning programs. Code learning programs today are mostly just a jumble of functions. Let's say we're controlling Elsa. elsaUp(); makes Elsa move up 10 pixels, elsaDown(); 10 pixels down, etc. Well, this teaches students close to nothing except for the absolute bare-bones aspect of code, and that's how code works, and possibly even the if(); command or two. Instead of having students be taught nothing more than how to use functions, tell them how to _make_ functions. For example, instead of just having elsaUp(); already be made, have them make it with: var elsaUp = function() { .................draw = function() { ................................background(255,255,255); ................................var px = x ................................var py = y ................................if (py - y = 10) { ................................................image(elsa,x,y,elsaSize,elsaSize); ................................................end ................................} ................................else { ................................................y ++; ................................................image(elsaWalking,x,y,elsaSize,elsaSize); ................................} .................} }
A modern computer science degree is basically a degree in discrete math. But when computer science was founded, it was much more closely related to being a science than it might be considered today. However, even if it has become more about proofs, math and logic, there still are investigations that require observing, and testing factual information to determine breakthroughs. As an example, consider quantum computing and it's development.
I don't really understand a computer cuz I don't have one but I love this video it is very respectful it teach you a lot about a computer so I hope when I have one this video would help me thank you
Most technically it's the study of algorithms, which are a very specific way of solving problems, but it's hard to define exactly what an algorithm is without getting a good ways into computer science.
MAlgMAlg1 That's linguistics. There is some overlap between computer science and linguistics, but they aren't the same thing. Also, the languages computer science uses have very little to do with natural language, they are mainly just a way of representing mathematical statements in a computable way.
I didn't say anything about natural language. I mean language in the formal sense, in the sense of logic and computation. Look at all the work in type theory and the million different incarnations of the lambda calculus.
Well, I'm a computer scientist (i.e. I work as an academic in computer science) and I study programming languages from a theoretical point of view and I am certainly no linguist. To say that the lambda or the pi calculus, dependent type theory and the Agda programming language, formal language theory and logic, are matters of linguistics is simply wrong. It's computer science. Now, I don't think you are completely wrong, of course the study of algorithms is also computer science. But don't discard the study of languages, and more specifically programming languages (practical and theoretical), as "not computer science".
No, I think it's by some folks over at Cornell, but they show NP-hardness/completeness of a lot of classic Nintendo video games, like Zelda, Metroid, Pokemon, and Donkey Kong.
He has Bachelor of science Degree in Engineering in electrical engineering and computer science It’s more like two degrees In 1 degree it’s a very hard degree to complete
As a sidenote, we don't know if prime factorization is NP-complete… and we don't know if it's P either! We only know it's NP. I'd be surprised if someone discovered it to be in P-and also if someone found it to be NP-complete, because this would mean quantum computers would solve NP-complete problems in polynomial time. If someone proofs that prime factorization is not P, and not NP-complete, we'd finally know once and for all that P != NP (via Ladner's theorem).
actual video and information begins at 0:55
Integer factorization is not NP complete though, it is not reducible to any other NP problems. Afaik
It's technically not known to be NP complete. It could be, I guess.
Probably just oversight, though.
That is to say, you are right as of right now and idk why I'm typing these comments.
Nice work! The animations did a great job of illustrating your points and it was well presented and explained. I really enjoyed it! :)
I'd like to take this opportunity to explain the biggest problem with almost all code learning programs. Code learning programs today are mostly just a jumble of functions. Let's say we're controlling Elsa. elsaUp(); makes Elsa move up 10 pixels, elsaDown(); 10 pixels down, etc. Well, this teaches students close to nothing except for the absolute bare-bones aspect of code, and that's how code works, and possibly even the if(); command or two. Instead of having students be taught nothing more than how to use functions, tell them how to _make_ functions. For example, instead of just having elsaUp(); already be made, have them make it with:
var elsaUp = function() {
.................draw = function() {
................................background(255,255,255);
................................var px = x
................................var py = y
................................if (py - y = 10) {
................................................image(elsa,x,y,elsaSize,elsaSize);
................................................end
................................}
................................else {
................................................y ++;
................................................image(elsaWalking,x,y,elsaSize,elsaSize);
................................}
.................}
}
This is an awesome video! I haven't found anything else that gives such a good intro to the P?=NP problem
i don't know a lot about computer science, but your visuals and the way you formulate the argument are very good
A modern computer science degree is basically a degree in discrete math. But when computer science was founded, it was much more closely related to being a science than it might be considered today. However, even if it has become more about proofs, math and logic, there still are investigations that require observing, and testing factual information to determine breakthroughs. As an example, consider quantum computing and it's development.
Thank you sir
I don't really understand a computer cuz I don't have one but I love this video it is very respectful it teach you a lot about a computer so I hope when I have one this video would help me thank you
Wow so how did you type this comment?
@@Kevin-cy2dr nice question
@@Kevin-cy2dr 😂😂
@@Kevin-cy2dr I use a phone
love how you put the youtube UI over it at ~3 10
i almost freaked out haha
Great work
Most technically it's the study of algorithms, which are a very specific way of solving problems, but it's hard to define exactly what an algorithm is without getting a good ways into computer science.
I disagree, it's also the study of languages!
MAlgMAlg1 That's linguistics. There is some overlap between computer science and linguistics, but they aren't the same thing. Also, the languages computer science uses have very little to do with natural language, they are mainly just a way of representing mathematical statements in a computable way.
I didn't say anything about natural language. I mean language in the formal sense, in the sense of logic and computation. Look at all the work in type theory and the million different incarnations of the lambda calculus.
MAlgMAlg1 I know what you're talking about, and you're still wrong. It's still either linguistics, or it's studying algorithms rather than languages.
Well, I'm a computer scientist (i.e. I work as an academic in computer science) and I study programming languages from a theoretical point of view and I am certainly no linguist. To say that the lambda or the pi calculus, dependent type theory and the Agda programming language, formal language theory and logic, are matters of linguistics is simply wrong. It's computer science.
Now, I don't think you are completely wrong, of course the study of algorithms is also computer science. But don't discard the study of
languages, and more specifically programming languages (practical and theoretical), as "not computer science".
What is the difference between "Computer Science" in English and "L'informatique" in French?
Anung Ariwibowo it’s the same thing generally.
1 come over 2 What are they
no outro? Really liked your definition of computer science
Is the Mario NP-Hard paper yours? I'm looking forward to reading that.
No, I think it's by some folks over at Cornell, but they show NP-hardness/completeness of a lot of classic Nintendo video games, like Zelda, Metroid, Pokemon, and Donkey Kong.
I never thought that computer science went far back
You're not the same guy as 3Blue1Brown are you?
Dang you're video is so great
Great editing and info
You had an opportunity to explain what Computer Science is and you botched it.
For everyone to know world's Richest Man Jeff Bezos also studied computer science
He has Bachelor of science Degree in Engineering in electrical engineering and computer science
It’s more like two degrees In 1 degree it’s a very hard degree to complete
Not understanding but I appreciate you tried maybe you can be more understandable? 😶
great video!
I don't have a computer but it seems very helpful so I hope soon to get one ☺️ 😜🤠 I like how it teaches you about it so fascinating
Thank you.
Yw
wait everybody says Computer science is all about solving problems,,, who create these problems first?
Problems are not created. They are discovered.
As a sidenote, we don't know if prime factorization is NP-complete… and we don't know if it's P either! We only know it's NP. I'd be surprised if someone discovered it to be in P-and also if someone found it to be NP-complete, because this would mean quantum computers would solve NP-complete problems in polynomial time. If someone proofs that prime factorization is not P, and not NP-complete, we'd finally know once and for all that P != NP (via Ladner's theorem).
use of computer
except mario isnt hard.
Thank sir you have discusses is comuter science
POV: you are here for an assignment over zoom
No
No
No
Sir smj nahi aa rehi h
ye wala channal ki bhi video aachi hai th-cam.com/channels/oEt3glB4rWSq5zEhSGhUWA.html?view_as=subscriber
❤️❤️❤️❤️❤️❤️❤️❤️❤️
This man has obviously never played a mario game.
Verynicecomlptersci
sorry man mario is not just a game!
You didn’t answer the question!
Most are here for online school
Is this even ur video ? 🤣
LOL
i only disliked because of that horrible introduction
Awesome, dude
Yes
This is so irrelavant