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Hey /sci/, I need some serious advice.
I just got an insanely lucky internship offer for about a half year down the line I believe.
It has to do with statistical modeling and I'd assume data analysis of epidemiological systems.
I'm finishing up my degree in applied math at a top(ish) uni.
I've taken a mathematical modeling course that was mostly differential equations that was mostly theory and little programming (discrete and continuous systems).
I've also taken nonlinear dynamics courses.
I have about 2-years programming experience in C++ and some linux skills. I don't know any other programming languages.
Questions:
Would you expect that probability theory courses and stochastic processes would help me a lot to prepare for this?
I have to choose between an optimization course and a machine learning course, do you think there's an obvious choice here?
Also, what are the most important skills you think I should pick up? (programming in R or SAS, more experience with data structures, etc)?
If I haven't given enough information for advice, sorry, just tell me to fuck off.
I'll check back up on this post in an hour or two.
Thanks a ton.
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>>9171111
First of all, sick quads bro.
Second, I am by no means a qualified person to give advice, but machine learning is the big thing right now as far as I can tell. Optimization - I don't know exactly what a class called that would cover it could be a lot of things, but all of those things are honestly pretty easy to learn yourself or just use by looking up the algorithm/results. R is also a really, really helpful thing to know, whether you actually need it for your job explicitly or not. That's my take anon.
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>>9171119
OP here. Thanks again :)
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