Hi,
I am a rising junior at a top 20 liberal arts school and am thinking about Grad school. I am currently a Math major with a Stats concentration and have some basic coding experience in STATA, Python, Java and SQL. M.S. programs in Data Science/Analytics are relatively new, so I was wondering if anyone can provide any insight on the courses/requirements.
Some programs I have been looking at include:
Northwestern M.S. in Analytics
UMD M.S. Marketing Analytics
Columbia M.S. in Data Science
Stanford MS in Statistics: Data Science
UVA M.S. in Data Science
Cornell MPS in Data Science
Thanks!
I know that for Columbia’s program the coursework is on the website: http://datascience.columbia.edu/course-inventory. The courses are drawn from engineering, statistics, computer science, and math, with some operations research thrown in. I would imagine that each program has a similar mix of fields/classes - some machine learning, some programming, some advanced statistics, some operations research/engineering/optimization/decision science-type stuff.
Thanks! I will check the link out. I was wondering if you had any idea about how competitive it is to get into these programs?
I don’t, personally. They’re all brand-new so I think there’s very little data on that. With Columbia - just a guess, since I went there for grad school in a different field - I do know that the departments that contribute to the program (statistics, OR/engineering, math, and CS) are all very competitive in their own right. On the other hand, the program is a cash cow - that doesn’t mean it’s not good (in fact, it is very good), but simply that it exists at least in part to generate revenue for the university. So I would imagine that it’s not as difficult to gain admission to as you might think. (As in, admissions rates may be in the 40-55% range rather than the 5-10% range like undergrad).
That’s just a guess, though!
Thank you for your input! I totally agree with you that these grad programs are just ways for schools to generate more revenue. I’ll look into them more before deciding what to apply to.