...then don't study computer science. I study CS and it's annoying when someone in a more math/logic oriented course is like "If I get a job at a tech company I won't need this". All that IS computer science, if you just wanna code, learn to code.
this post was submitted on 19 Jul 2023
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The problem is a lot of people who want to learn to code, and are conditioned to desire the college route of education, don't actually know that there is a difference and that you can be completely self-taught in the field without ever stepping foot in a university.
We're not closing schools despite having libraries and the internet, having (good) teachers is useful to learn faster and get pushed further. There are some good programming schools that can make it more efficient for you. I think the main problem is rather the insane cost of higher education in the USA which create anxiety about being certain that you can repay it in the future it may open for you. It is sad.
Can you get well paying coding jobs with upward mobility without at least a BA in CS?
It's harder to break into but I make 150k and barely graduated high school. Software engineering is largely a field that doesn't care about degrees but about ability. It's harder these days to break into the field than it was 10 years ago when I did but it's absolutely still possible
I have a fine arts degree and I'm a lead dev 🤷♂️
Maybe not what you're asking but people with a non-CS M.Sc or PhD commonly switch to coding, especially in the data fields.
I've never been to college and my job title today is Software Architect, I've been doing this for nearly 20 years.
It was extremely hard at first to get a job because everyone wanted a BA, but that was also 20 years ago. Once I had some experience and could clearly demonstrate my capabilities they were more open to hiring me. The thing a degree shows is that you have some level of experience and commitment, but the reality is a BA in CompSci doesn't actually prepare you for the reality of 99% of software development.
I think most companies these days have come to realize this. Unless you're trying to apply to one of the FANG corps (or whatever the acronym is now) you'll be just fine if you have a decent portfolio and can demonstrate an understanding of the fundamentals.
If you entered the field 10 years ago, sure. If you're trying to enter the field now, I have bad news...
4 years later: "this button is the wrong color. fix it ASAP"
I was interviewed with complex logic problems and a rigorous testing of my domain knowledge.
Most of what I do is updating copy and images.
This hurts so much because it's my life :(
I wonder how many in that class will ever need to think about multitape Turing machines ever again.
The point of these lectures is mostly not to teach how to work with Turing machines, it is to understand the theoretical limits of computers. The Turing machine is just a simple to describe and well-studied tool used to explore that.
For example, are there things there that cannot be computed on a computer, no matter for how long it computes? What about if the computer is able to make guesses along the way, can it compute more? Because of this comic, no — it would only be a lot faster.
Arguably, many programmers can do their job even without knowing any of that. But it certainly helps with seeing the big picture.
Arguably, a much more important thing for the students to learn is the limits of humans. The limits of the computer will never be a problem for 99% of these students or they'll just learn on the job the types of problems they're good at solving and the ones that aren't.
The limits of computers would be the same as the limits for humans. We have no reason to think the human brain has a stronger computation power than a Turing machine.
So, in a way, learning about the limits of computers is the exact same as learning the limits of humans.
But also, learning what the limits of computers are is absolutely relevant. You get asked to create an algorithm for a problem and its useful to be able to figure out whether it actually is solvable, or how fast it theoretically can be. Avoids wasting everyone's time trying to build an infinite loop detector.
The "limits of humans" I was referring to were things like:
- How long can you push a deadline before someone starts to get really mad
- How many dark patterns you can cram into an app before the users stop using it
- The extremes of human stupidity
👍
..none of which would be relevant for most people working in back-end, which would be most people that take compsci.
I would hate to go to a compsci study and learn management instead. It's not what I signed up for.
University also shouldn't just be a job training program.
Two govt spooks are hunting a dangerous fugitive who is also a humanities graduate. He escapes into a sprawling maze of tunnels. "It's hopeless," one of the spooks says. But the other simply says, "Watch." then proclaims loudly, "studying linear algebra is important because of its use in stochastic processes and image manipulation." Before he finishes the sentence, the fugitive emerges back out the tunnel and shouts, "but what's even more important --" and is immediately knocked unconscious and taken for questioning
Never used a Turing machine, but I have a project that generates NFAs and converts them to DFAs so they run faster.
How does one convert a No Fear Article into a Definitely Fear Article?
I thought it was Non-Fungible Articles and Decentralised Federated Articles
But you can make games that much more interesting if your algorithms are on point.
Otherwise it's all "well I don't know why it generated map that's insane". Or "well AI has this weird bug but I don't understand where it's coming from".
Abstruse Goose!! 🖤
I’m grateful to this strip because reading it caused me to learn the correct spelling of “abstruse”. I’ve never heard anyone say the word, and for some reason I had always read it as “abtruse”, without the first S.
I loved learning lambda calculus (though for me it was super hard)
I never really understood the point of Lambda calculus. Why have an anonymous function? I thought it was good practice to meticulously segment code into functions and subroutines and call them as needed, rather than have some psuedo-function embedded somewhere.
I suppose it has to do with being stateless.
I just loved learning about lambda calculus.
I think the idea is to remove complexity by never dealing with state, so you just have one long reduction till you get to the final state...
But someone who's more into lambdas etc should speak about this and not me (a weirdo)
I think you're confusing lambdas with lambda calculus. Lambda calculus is more than just anonymous functions.
To put it extremely simply, let's just say functional programming (the implementation of lambda calculus) is code with functions as data and without shared mutable state (or side effects).
The first one increases expressiveness tremendously, the second one increases safety and optimization. Of course, you don't need to write anonymous functions in a functional language if you don't want to.
As for why those "pseudo-functions" are useful, you're probably thinking of closures, which capture state from the context they are defined in. That is pretty useful. But it's not the whole reason lambda calculus exists.
See the other comments about lambdas vs. lambda calculus, but lambdas are supposed to be for incredibly simple tasks that don't need a full function definition, things that could be done in a line or two, like simple comparisons or calling another function. This is most useful for abstractions like list filtering, mapping, folding/reducing, etc. where you usually don't need a very advanced function call.
I was always taught in classes that if your lambda needs more than just the return statement, it should probably be its own function.
I did games technology at university. We had a module that was just playing board games and eventually making one. Also did an unreal engine module that ended with making a game and a cinematic.
It was awesome.
Sipser is an absolute banger of a book though.
I read it cover-to-cover like fifteen years ago. I've lost most of that knowledge since I haven't touched it in so long, but I remember I really enjoyed it.
Since when were Turing machines ever nondeterministic?
Hm, I wonder if I could make these students more miserable by introducing a CPU that permits static operation, then clocking that with a true random number generator?
So now it has output that is deterministic from the standpoint of the CPU but nondeterministic to an outside observer. Probably wouldn't affect the O(n) notation though, come to think of it. It would be funny though.