Why is math required for a computer science degree?

[Anonymous]

9:56 here - sorry for all the typos. I was on my phone. I am NOW a practicing engineer, not "not a practicing engineer" And weed-out, not week... etc...

[Anonymous]

On the point of kids determining they are not "mathy" or "technical" -- I find this even with my son based on the fact he's around a lot of really smart kids here in NOVA. He's always scored 130-140 on things like Cogat and WISC quant sections, got a 720 first try on the math portion of SAT. By any measure, this puts him in the top few percentile in basic quantitative thinking--and enough capacity to do the math/science in any undergrad STEM degree. He's not some crazy math super-star or anything, but in the large view, he would be considered to have strong quantitative skills.

But he's young for his grade and opted to do Algebra H in 8th grade rather than 7th, despite qualifying for it based on the Iowa test. He's gotten A's and B's in all his math classes through AP Calc. But since his only "B's" have been in advanced math and science courses and he hasn't done a post-calc hs course, and is a leader in history/literature etc. He most definitely thinks of himself as ineligible for STEM majors. This would be fine except he also really loved chemistry and has always loved building and designing things. I don't want him to do STEM if it's not his thing, but it bugs me that he's decided based on being around a lot of high achieving peers that it's not really a viable option before he even tries out some college courses. I've tried walking him through this thinking, but it's hard.

[Anonymous]

Computer Engineering: yes, you need math

Computer Science: NO, you do not need math. There are many people at my work place who are programming with Python/Java and they do not use math higher than Algebra I.

[Anonymous]

Anonymous wrote:Computer Engineering: yes, you need math

Computer Science: NO, you do not need math. There are many people at my work place who are programming with Python/Java and they do not use math higher than Algebra I.

I have degrees in both - undergrad in Comp Sci and grad in Computer Engineering - you have it backwards.

[Anonymous]

Anonymous wrote:Computer Engineering: yes, you need math

Computer Science: NO, you do not need math. There are many people at my work place who are programming with Python/Java and they do not use math higher than Algebra I.

[Anonymous]

Anonymous wrote:

Anonymous wrote:Computer Engineering: yes, you need math

Computer Science: NO, you do not need math. There are many people at my work place who are programming with Python/Java and they do not use math higher than Algebra I.

Agree with the eyeroll. if you want to get into computer science, computer engineering or game design you need advanced algebra and calculus for coding. It's all math at the upper levels.

[Anonymous]

Anonymous wrote:Computer Engineering: yes, you need math

Computer Science: NO, you do not need math. There are many people at my work place who are programming with Python/Java and they do not use math higher than Algebra I.

This is completely reversed.
Upper level computer science is almost indistinguishable from math.
Computer engineering doesn't require that level of theory and ends at applied courses like calculus and some physics for engineers.

[Anonymous]

I have no idea what people are talking about. I am working as a software developer and I never use math in my daily work.

[Anonymous]

Anonymous wrote:I have no idea what people are talking about. I am working as a software developer and I never use math in my daily work.

It really depends on what you’re doing. Machine learning, graph analytics, signal processing, simulations etc., all require a lot of math. Standard full stack web development doesn’t really require much, other than boolean logic and understanding algorithmic complexity. I will say though, that it’s been my experience that those who are good with math are also good with the analytical problem solving skills necessary to be an excellent developer.

Your point is valid though; you can work in some (perhaps many) domains in CS without doing a lot of math.

[Anonymous]

Anonymous wrote:

Anonymous wrote:I have no idea what people are talking about. I am working as a software developer and I never use math in my daily work.

It really depends on what you’re doing. Machine learning, graph analytics, signal processing, simulations etc., all require a lot of math. Standard full stack web development doesn’t really require much, other than boolean logic and understanding algorithmic complexity. I will say though, that it’s been my experience that those who are good with math are also good with the analytical problem solving skills necessary to be an excellent developer.

Your point is valid though; you can work in some (perhaps many) domains in CS without doing a lot of math.

Correct. My son is doing computer science and taking enough math classes that he is double majoring in math w concentration in statistics.

[Anonymous]

Upper level computer science courses, such as algorithms, theory of computation, etc. draw techniques from a lot of math classes, especially combinatorics and discrete math. The modern instantiations of AI courses (with the machine learning focus) will draw a lot from calculus and differential equations.

All that being said, computer science is not software engineering. Both can require varied levels of math, but CS definitely requires more as you go into the theory heavy sides of the discipline.

Software engineering is a lot more about system design, architecture, principles of testing, effective coding techniques, etc. There are a lot of CS grads who end up doing software engineering. Folks that picked up some coding from other disciplines also find their way into software engineering. All-in-all, it's a pretty good profession for people that like to problem solve and are willing to put in the time to keep their technical skills up to date.

[Anonymous]

Anonymous wrote:

Anonymous wrote:I have no idea what people are talking about. I am working as a software developer and I never use math in my daily work.

It really depends on what you’re doing. Machine learning, graph analytics, signal processing, simulations etc., all require a lot of math. Standard full stack web development doesn’t really require much, other than boolean logic and understanding algorithmic complexity. I will say though, that it’s been my experience that those who are good with math are also good with the analytical problem solving skills necessary to be an excellent developer.

Your point is valid though; you can work in some (perhaps many) domains in CS without doing a lot of math.

- Myself: work for a gov. contractor in java/python programming and it does not require any math
- my wife: work for a gov. contractor in cyber security and she does not use math
-my sister: work for the census as computer scientist and she does not use math
-my brother: work for a gov contractor with the DoD as system administrator and no math
-my cousin(s): Fed and gov. contractors in IT field and no math,

Yes, you will use lot of math if you work in CS field that are specialized in R&D but for 99.999% of the CS and IT jobs in the DMV, no math is needed.

[Anonymous]

Anonymous wrote:

Anonymous wrote:I have no idea what people are talking about. I am working as a software developer and I never use math in my daily work.

It really depends on what you’re doing. Machine learning, graph analytics, signal processing, simulations etc., all require a lot of math. Standard full stack web development doesn’t really require much, other than boolean logic and understanding algorithmic complexity. I will say though, that it’s been my experience that those who are good with math are also good with the analytical problem solving skills necessary to be an excellent developer.

Your point is valid though; you can work in some (perhaps many) domains in CS without doing a lot of math.

I would agree with this. But I would also say there is a subset of excellent developers who are amazing with analytic problem solving who--for whatever reason--didn't gel with the abstractness of math as it is currently taught (or had weak foundational math education or internalized some stereotypes about their math abilities...). I can picture a post HS calculus math series where mathematical/logical principles are extracted out from applied computer science problems that might really serve a large swath of folks better. I think getting to the abstraction is necessary for generalizable knowledge appropriate to a CS degree, but maybe you don't have to go traditional math route to get there.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:I have no idea what people are talking about. I am working as a software developer and I never use math in my daily work.

It really depends on what you’re doing. Machine learning, graph analytics, signal processing, simulations etc., all require a lot of math. Standard full stack web development doesn’t really require much, other than boolean logic and understanding algorithmic complexity. I will say though, that it’s been my experience that those who are good with math are also good with the analytical problem solving skills necessary to be an excellent developer.

Your point is valid though; you can work in some (perhaps many) domains in CS without doing a lot of math.

I would agree with this. But I would also say there is a subset of excellent developers who are amazing with analytic problem solving who--for whatever reason--didn't gel with the abstractness of math as it is currently taught (or had weak foundational math education or internalized some stereotypes about their math abilities...). I can picture a post HS calculus math series where mathematical/logical principles are extracted out from applied computer science problems that might really serve a large swath of folks better. I think getting to the abstraction is necessary for generalizable knowledge appropriate to a CS degree, but maybe you don't have to go traditional math route to get there.

It's not necessary.

[Anonymous]

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:I have no idea what people are talking about. I am working as a software developer and I never use math in my daily work.

It really depends on what you’re doing. Machine learning, graph analytics, signal processing, simulations etc., all require a lot of math. Standard full stack web development doesn’t really require much, other than boolean logic and understanding algorithmic complexity. I will say though, that it’s been my experience that those who are good with math are also good with the analytical problem solving skills necessary to be an excellent developer.

Your point is valid though; you can work in some (perhaps many) domains in CS without doing a lot of math.

I would agree with this. But I would also say there is a subset of excellent developers who are amazing with analytic problem solving who--for whatever reason--didn't gel with the abstractness of math as it is currently taught (or had weak foundational math education or internalized some stereotypes about their math abilities...). I can picture a post HS calculus math series where mathematical/logical principles are extracted out from applied computer science problems that might really serve a large swath of folks better. I think getting to the abstraction is necessary for generalizable knowledge appropriate to a CS degree, but maybe you don't have to go traditional math route to get there.

It's not necessary.

Are you claiming abstraction is not necessary for generalizable knowledge appropriate to a CS degree or that abstraction is not necessary for many CS jobs?
I guess I'm of the belief that a university degree should develop some generalized set of skills/capacities that characterize a discipline/field--and for CS math/logic is a core part of that. Otherwise you can just get by with on-the-job training on whatever tools you are going to use first. So I think shouldn't need a university degree to do a lot CS jobs, but if there is a degree it should have some abstracted, generalizable knowledge and skills along with the practicalities.