[earl]

.02 from someone who does data analysis / ML and has an undergrad in math:

A math undergrad is a nearly total waste of time. If you want to do data analysis, learn to do data analysis. Real analysis and proofs and abstract algebra and diffeq are fascinating yet utter wastes of time.

If you want to learn useful stuff, take: applied calc, applied linear algebra, applied probability, applied stats, applied ML. And nothing else. All the skills you build proving stuff are, at best, tangential. And you don't need a bit of it to do things like derive gibbs samplers or EM samplers.

If you can take an activity such as someone interacting with ads, model that as a graphical model, derive a gibbs sampler and implement it, you'll be worlds ahead of even most grad students. Focus on getting there and it should be great for your career. But a math degree is just a shiny distraction.

Oh, and one more thing: if you want to work in a particular area, then a degree in that area may be useful. Eg bio, genetics, chemistry, fluids, optics, etc.

edit2: Please don't think I'm arguing against you getting a math degree. If you want one, get one. Just understand it's probably at least 80% intellectual masturbation instead of job skills. For example, as far as I can see in production machine learning, there is virtually no integration. Oh there are integrals all over the place but none of them are feasible and they'll all have to be numerically evaluated or worked around. So all those integration skills people spend endless hours learning are basically useless because the real world has virtually zero nice integrals. So understanding how to manipulate integrals and how to numerically evaluate them is very valuable, but not well covered in virtually all calc classes.

edit3: consider looking at the community colleges in your state. They often are stupid cheap and offer online courses.

[tgrass]

Regarding your opening line: leave it to a mathematician to forgo units. I assume you meant $0.02.

:)

- a sarcastic engineer.

[excuse-me]

As a physicist this always annoyed me about about maths lectures.

You spend half of your physics degree learning certain classes of integrals when in practice everyone you really need to solve is done numerically. Yet you get half a class on numerical methods it you're lucky