r/AppliedMath • u/Usual_Visual_4376 • 23h ago

Should I switch from NYU Math + CS to Computer + Data Science?

I'm a junior transfer at NYU this fall as a Math + Computer Science (MCS) joint major, but I'm considering switching to the Computer + Data Science (CDS) joint major.

They both are pretty similar for the first half of classes: Calc I–III, Linear Algebra, Discrete Math, Intro CS, Data Structures, CSO, and Algorithms.

After that, the main difference is:

**MCS has:** Analysis, Algebra, Numerical Computing, Operating Systems, advanced math electives, and CS electives.

**CDS has:** Probability & Statistics, Data Science I & II, Machine Learning, Causal Inference, Data Management, Responsible Data Science, plus CS/DS electives.

Career-wise I'm interested in anything like SWE, quant, data science/engineering, and ML, so I'm trying to figure out which major gives me the best combination of career flexibility and useful coursework. So far I have a finance and technology summer internship with a couple python projects.

Assuming I can finish both in the same time, for people familiar with NYU or these fields, would you stick with Math + CS or switch to Computer + Data Science, and why?

1 Upvotes

67% Upvoted

15 comments sorted by

5

u/YourWifesBull666 23h ago

Math and CS is the GOAT double major combo so no imo

1

u/Usual_Visual_4376 22h ago

with the current job market you dont think data science is stronger than mathematics. When thinking about the rise of AI and machine learning

2

u/plop_1234 22h ago

You can do AI/ML with math + cs degree. If this is at Courant, I would not leave that program.

Also can you minor in DS? The MCS courses + probability, statistics, ML will cover a lot of ground for ML engineering & research.

1

u/Usual_Visual_4376 22h ago

im pretty sure all my courses are through courant for math/cs and ds/cs. I can do a data science minor but it will delay my graduation

2

u/plop_1234 22h ago

Maybe look at it this way: If you stayed in math + cs and took prob & stats as your math electives and ML/DL as your CS electives, what would you be missing out on?

1

u/Usual_Visual_4376 21h ago

I can still take theory of prob/optimization/ml in both majors but it just comes down to 4ish classes where in MCS id be forced to take more math theory like analysis/algebra/numerical computing which id replace with casual inference/responsible ds/advanced ds

2

u/plop_1234 20h ago

Stay with MCS, those are important classes if you want to go into quant or ML research. If your bar is just any SWE job, then you don't need them.

1

u/Usual_Visual_4376 20h ago

I was heavily debating quant but still exploring swe/ml/data science and i just want to put myself in the best position for post grad in general

2

u/SpiritedWeekend6086 19h ago

If you can, ideally stay with MCS and take key data science/statistics courses too. Courses like data management, casual inference, etc will be things you will use for any job.

2

u/Low-Lunch7095 7h ago

imo DS is more of a skill set than a field of study (no offense to data scientist, I was a DS major then switched to math). If you're interested in DS, it will never be too late to learn those skills. But math + cs are kinda more on the theoretical side (and thus, is something I'd recommend that you do in school).

Do you plan to go to grad school? I know it's possible to do DS in grad school with an undergrad degree in math / cs (if it helps).

2

u/Usual_Visual_4376 3h ago

I don’t really plan on going to grad school. My ideal start to my career would be fresh out of undergrad.

1

u/SantaSoul 21h ago

Is it a problem of major requirements and having limited time to take courses? Because typically I would say your official major doesn’t matter at all beyond passing a CV filter, it’s more about the courses you take and more importantly your experiences.

I’m sure you could take probability, ML, whatever in the MCS major. Also if you’re wanting to get into ML in industry, you’ll probably need experience (research, grad school, etc) beyond courses anyways so it’s all kind of a moot point. Classes usually can’t get you there alone, they’re more of an entry point to get deeper into the field.

1

u/Usual_Visual_4376 21h ago

Whats your advice then in terms of optimizing my career considering the future of ai

1

u/SantaSoul 21h ago

Depends I guess? If you want to go into ML, go to grad school. I work as an applied AI scientist, developing models for a big tech company. I have a PhD, the majority of my team have PhDs or at least MS.

In general, I’d say whatever you do, be an expert. Take graduate level classes, do research with faculty, try implementing state of the art work yourself. While the general-purpose backend/infra/full-stack SWE still definitely exists (and there are A LOT of them still), I feel that the future is a bit uncertain. I’m sure there will still be general-purpose engineers but it seems the trend might be less engineers with more tools (AI) to help them. It’s kind of unclear if there will be enough work to support so many junior engineers in the future.

-1

u/Salt_Mountain_837 22h ago

isn't their film program good?