ITT we post our major, what year we're in and our current gpa

>3.4
JUST

Math
4th year
3.7

Nearly every CS/math double does the math education track.

Freshman, Math 3.7 (first qtr.) gpa

Yup, because actual math is too hard for them.

>freshman
>anything less than a 4.0
drop out now

Enjoy the GPA while you have it.

It's good relative to my school and p. good relative to everyone else in my math class (class size ~15).

Well are you in any advanced classes or just standard classes?

Yeah my math is honors.

Sci really has a hard on for putting down cs. Why in the hell would any cs/math major do the education track? I'm focusing on combinatorics and graph theory, but that does not mean I don't take bread and butter courses like real analysis, abstract algebra, and etc.

I just worked for it. I'm not very smart but I do have a work ethic.

But like how many years ahead are you?

Also, what is honors math? Like for what course?

It's an honors class offered only to first years. It's an intro to real analysis/proof based calc class whatever you want to call it. We use something called the moore method en.wikipedia.org/wiki/Moore_method .

Oh. That's alright

Comp E w/ Physics minor
Senior
3.4

Math/CS
4th year with grad classes
>3.9

CS is just as retarded as everyone says and I regret wasting my time on it. It should have stayed as my hobby.

CS/math here also.

You plan on doing grad school or what? I know most of cs is "dumb" but the more theory stuff is fun.

BioChemistry
Junior Year
>3.5

I fucked up a couple classes and it pulled my GPA down. I did well in most other classes, but I am also pursuing a math minor. I got a B in linear algebra, my first proof based course, and I have 5 more proof based courses, except now they're going to be upper division.

Any study tips from guys with better gpas and more experience? I really want to do well

Grad school for math. Really interested in algebraic geometry.

Ah. Yeah cs was a waste 4 u desu. But if it makes you feel better, even if people disagree, doing a cs degree can serve as a good "back up".

>but that does not mean I don't take bread and butter courses like real analysis, abstract algebra, and etc.

CS majors tend to take watered down version of analysis and algebra that use books like Gaughan, Ross, Pinter, and Gallian instead of the typical books like Rudin, Pugh, Artin and Herstein.

That's true. I actually work as a programmer right now and make good money with it, but I don't want this to be my career.

My undergrad algebra course used Gallian but then Dummit & Foot for the graduate section (which is basically the same.)

They have legitimate algebra courses after that

>doing a cs degree can serve as a good "back up"

No. You can get a code monkey job with any degree.

Idk how this only applies to cs majors, but desu If you are not doing TCS then all you need is lin alg and discrete math. If you are doing TCS then you should try to get the best possible math education, it's better probably to get a math major and do a cs minior but a cs major is very marketable so it's a good back up.

cstheory.stackexchange.com/q/1920

>a cs major is very marketable

Employers are wising up to how bullshit the degree is.

>Dummit & Foot for the graduate

Your school is incredibly shitty.

Source?

>there are legitimate algebra courses after that

Lern 2 reed

Chem
2nd year
2.87

If this was how it would end next semester I would have killed myself by now.

>how do i google

usajobs.gov/GetJob/ViewDetails/458707100/

Aren't those requirements fulfilled by any decent cs program? Since there asking for a data scientist, it makes sense they don't want some guy with a software engineering degree.

>CS doesn't even do diff eq nor linear algebra at my school. They don't even do calc 3 ffs.

Epic post man.

>Mathematics Requirements in Computer Science
>While nearly all undergraduate programs in computer science include mathematics courses in their curricula, the full set of such requirements varies broadly by institution due to a number of factors. For example, whether or not a CS program is housed in a School of Engineering can directly influence the requirements for courses on calculus and/or differential equations, even if such courses include far more material in these areas than is generally needed for most CS majors. As a result, CS2013 only specifies mathematical requirements that we believe are directly relevant for the large majority of all CS undergraduates (for example, elements of set theory, logic, and discrete probability, among others). These mathematics requirements are specified in the Body of Knowledge primarily in the Discrete Structures (DS) Knowledge Area.

>We recognize that general facility with mathematics is an important requirement for all CS students. Still, CS2013 distinguishes between the foundational mathematics that are likely to impact many parts of computer science—and are included in the CS2013 Body of Knowledge—from those that, while still important, may be most directly relevant to specific areas within computing. For example, an understanding of linear algebra plays a critical role in some areas of computing such as graphics and the analysis of graph algorithms. However, linear algebra would not necessarily be a requirement for all areas of computing (indeed, many high quality CS programs do not have an explicit linear algebra requirement). Similarly, while we do note a growing trend in the use of probability and statistics in computing and believe that this trend is likely to continue in the future, we still believe it is not necessary for all CS programs to require a full course in probability theory for all majors.
>acm.org/education/curricula-recommendations

>The Computer Engineering Task Force makes the following recommendations with respect to the mathematical content of the computer engineering curriculum.
>Discrete structures: All students need knowledge of the mathematical principles of discrete structures and exposure to related tools. All programs should include enough exposure to this area to cover the core topics specified in the computer engineering body of knowledge.
>Differential and integral calculus: The calculus is required to support such computer engineering material as communications theory, signals and systems, and analog electronics and it is fundamental to all engineering programs.
>Probability and statistics: These related topics underpin considerations of reliability, safety, dependence, and various other concepts of concern to the computer engineer. Many programs will have students take an existing course in probability and statistics; some programs may allow some students to study less than a full semester course in the subject. Regardless of the implementation, all students should get at least some brief exposure to discrete and continuous probability, stochastic processes, sampling distributions, estimation, hypothesis testing, and correlation and regression, as specified in the computer engineering body of knowledge.
>Additional mathematics: Students should take additional mathematics to develop their sophistication in this area and to support classes in topics such as communications theory, security, signals and systems, analog electronics, and artificial intelligence. That mathematics might consist of courses in any number of areas, including further calculus, differential equations, transform theory, linear algebra, numerical methods, complex variables, geometry, number theory, or symbolic logic.

>Software Engineering Mathematics and Statistics
>Software engineering makes little direct use of traditional continuous mathematics, although such knowledge may be necessary when developing software for some application domains as well as when learning statistics. Like computer science, software engineering makes use of discrete mathematical formalisms and concepts where necessary, such as when modeling the interactions and potential inconsistencies among different requirements and design solutions, modeling artifacts for test design, and modeling behavior for security analysis.
>Statistics also have a role in software engineering. Activities such as cost modeling and planning require an understanding of probability, and interpretation of the growing body of empirical knowledge similarly needs familiarity with issues such as significance and statistical power. In addition, the interactions of a software artifact with other system elements often leads to behavior that is nondeterministic and, hence, best described using statistical models. Because these are all applications of statistics and probability, a calculus-based treatment is not necessarily required.
>acm.org/binaries/content/assets/education/se2014.pdf

So what hum did you take?

>tl;dr
SE = college algebra, discrete math, business stats
CS = precalculus, discrete math, business stats
CE = Vector calculus, linear algebra, DEs, probability, Fourier transforms, discrete math, information theory, control theory, numerical analysis, etc

Go check out a state school like ucf or Arizona state and tell me if cs does not take up to lin alg and vector calc.

>C course
>a complete course about a specific technology without any theoretical fundament
kek

Yeah, CS programs differ between universities, which means, that you need to pick a good CS program is more important than i.e. a good math program.

toc*

Got ya!

i admit, you got me

Depends on university, mine required you to take analysis, discrete maths, linear algebra, stochastics and numeric

Doesn't this prove 's point though?

Biomedical Science
4th Year
4.0

What the averages like at your unis Veeky Forums? The average in the ME department here is around 3.0.

First year math, 5.0 average

Physics
Last year
>Not americuck
7.0/10

how do i reset my GPA and start college over from ground zero
do i have to get a new identity

Mathematics
2nd
3.85

Transfer to another university, or graduate and re-enroll as a post-bac.

I did pure math undergrad and got a terrible GPA because I never studied or put the effort into the degree. Regretted it later and figured I screwed my chances up for PhD studies despite knowing I'm fully capable. I started studying after graduation and understood shit I didn't understand then and re-enrolled at another college as a post-bac (non-degree student) taking courses to improve my GPA and get admitted to PhD programs. This semester I made a 100% in my course and after final have a good shot at a 4.0.

I spoke to one professor about my grades and he said the only transcript they look at will be my last one and since I am going to the school I want to apply for a PhD for, this is very good news.

Chem
3rd yeard
2.65

lel how fucked am I?

not at all, GPA doesn't matter

applied math and stat with a minor in spanish. 3.32.

Depends on what you want to do. If you're looking at med school for some reason you're pretty much screwed, otherwise try looking for research opportunities to have a dog in the race. Most employers are looking for at least a 3.0 but if you can market your skills in a clever way you'll be alright.

I did quite a research in organometallics with my professor this year, and i plan on doing an internship next year. Would that give me a good chance of a decent job in the long run? I also plan on doing water purification treatments as a career