Tfw switched from math to compsci since it seemed more fun

>tfw switched from math to compsci since it seemed more fun
>tfw realised that Veeky Forums was right and I literally could just study math and learn compsci on the side
W-well I can atleast take 2 bachelors, shame about throwing away so many courses to the compsci meme

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Well meme'd

>implying you can't learn math on the side
Just switch back to maths in grad school

>Implying upper div CS courses are easy
Good luck OP

says the meme

They are.

only a CS major would know about the level of difficulty of the courses.
Why are you meming yourself user? Are u only in it for the money?

>Just switch back to maths in grad school

This is like learning how to be a car mechanic in trade school to then go get a PhD in Experimental Physics.

It is simply not the same. In CS you will learn math that is comparatively useless. The reason we mock those discrete math books is because they take a bunch of topics in math that belong in different fields that ought to be studied separately (if you wish to do research) and then merge only their most obvious theorems (without proof, obviously) to compile a random elementary math manual.

You cannot go to fucking grad school in mathematics knowing only an elementary math manual.

>C++
>Java

i warned you.

cs is better if you want to work in the industry

That is simply not true. I've had plenty of professors that went to Math in graduate school from CS in undergrad. Stop trying to pretend Math is hard. Do you really think Math is hard, brainlet?

businessinsider.com/what-is-rokos-basilisk-2014-8

0/10

click bait motherfucker

A major/minor was always the best option if you want to earn money

>I cannot form any semblance of an argument with my brainlet mind so I'm going to assume the one I'm replying to is throwing out some bait.

Sounds about right with the people from Veeky Forums.

For some actual discussion: I read Sipser's book over the summer and am currently using Arora/Barak's book right now. While the material is obviously more advanced, it's full of typos and I feel not very good quality writing.

>my college recommends both Epp and Rosen

What's wrong with those?

>tfw when first semester was java with bluej
Fucking hell man, its the useless shit

how does probability figure into CS?

>>tfw switched from math to compsci since it seemed more fun

ahahahahahah

The image is a troll. That Sedgewick and Flajolet book doesn't even teach Algorithms. It's a math book.

>algorithms
>not math

3.14/10

I understand your point, but if you actually owned and used the book like I do, you would know what I'm talking about. The book does not teach algorithms at all, it teaches discrete math, asymptotics and gives a simple intro to analytic combinatorics.

You are only taking shit tier courses if you have this problem.

I'm doing two degrees (BSc pure math and BSc comp sci) and the more challenging and interesting courses I've taken have been in the comp sci program (and I've already finished the pure math degree). Thing is that a math degree is pretty fleshed out in terms of what one has to take (so many abstract algebra courses, so many analysis courses, etc..) but a comp sci degree is very open ended and has very few explicit requirements. So the courses one comp sci student takes can differ vastly from those another student takes and these will also affect the courses outside of the department they have to take (eg. Crypto people have to take abstract algebra, category theory people have to know a good amount of pure math, type theory people have to know some pure math and some formal logic, etc...). A student who works in information security doesn't really have as much use for high level abstractions as they do for low level implementation details, a student who works with graphics engines won't really care about category theory, etc...


If you're interested in mathy courses then take those. Take category theory, type theory (might be called something along the lines of functional programming foundations and is not to be confused with the programming paradigms course), computational algebra, recursive function theory (typically offered as a second course in computability), compilers, etc..

Nigga are you implying that math majors take a different discrete math course or that discrete math is the only math course a comp sci student ever takes?

It's used a lot all over artificial intelligence (eg. find the translation with the highest probability of being correct). It's also prominent in it's subfields like natural language processing (NLP) and machine learning (there it's used alongside convex analysis).

It also appears less prominently in some data structure theory (eg. Computing how long it will take to insert/delete/search for data in a data structure that is populated in a random way, checking for collisions on hashes, etc..) and in some infosec theory (eg. How good is your password).

You are 100% correct.

Sedgwick has an algorithms book that he uses to teach an algorithms course (I think it's an year long course as well). He also has an analysis of algorithms book that he uses to teach a more advanced analysis of algorithms course (that has algorithms as a prerequisite. Only a moron who hasn't read the book would think it is meant to be used for an intro algorithms course.