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MS in CS vs. Data Science


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I've been wrestling with the following choice and am hoping for some outside opinions.

 - My Background

  • Engineering undergrad with some programming coursework
  • 2 years analyst experience (using R, SAS, SQL, some Python)
  • My current professional interests fall within data science

 - University of Chicago Masters Program in Computer Science:

  • An MS in CS would open a number of doors, including but not limited to DS
  • Program accepts applicants w/o a formal CS background (i.e., me) so it's definitely not the most in-depth MS in CS around, but still seems to yield strong results in industry
  • Have the ability to specialize in Data Analytics (courses in stochastics, ML, data modeling)
  • Curriculum link

 - University of Michigan MS in Data Science

  • Concerned that an MS in DS may limit long term career options, but would be able to take courses within the Stats/Biostats/CS departments which are well-respected.
  • Curriculum doesn't cover all of the CS bases that UofC would, but leaves room for interesting electives.

Both programs are fully on campus and do not require a thesis.  MS in DS programs are seemingly quite popular, and I feel extremely lucky to have gotten into UofM; on the other hand, I feel like CS has a bit more visibility and long-term versatility in the job market.  UofM is the more competitive program (to the extent that matters at all) and is academically probably more prestigious with both their statistics and CS departments being highly ranked.

Any thoughts or words of advice are appreciated!

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