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Top 10 CS masters program w/out undergrad research


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I just graduated with two bachelor's degrees in biology and psychology. But, I want to go to graduate school to study data science or machine learning. I started taking pre-reqs for ML a year and a half ago. (Discrete mathematics, multivariate calculus, linear algebra, probability theory) I have all A's currently, and I had a 3.955 undergrad GPA. (But I don't know if that matters.) I think that the biggest obstacle for me will be the fact that I have not done any CS research, and I won't have time to do any before I apply for a masters program. But, I have done a year of neuroscience research, wrote an undergad thesis, presented a poster, and I have a paper submitted. Do you think it's feasible for me to get into a top 10 machine learning grad school (Stanford, Carnegie Melon, MIT, Berkeley, etc.) even though I have no CS research experience? Do you think that the fact that I've done neuroscience research will be enough to show that I have research potential?

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I think in general, Master's programs don't weigh research as heavily (vs PhD programs). That said, they will probably expect some level of background in CS/programming.

For example, this is from Stanford MSCS (http://scpd.stanford.edu/public/category/courseCategoryCertificateProfile.do?method=load&certificateId=1240861):

Expected Background

The MSCS program assumes that all entering students have acquired the foundations of computer science at the level of an undergrad minor. At Stanford, these foundations are represented by the following courses, which are considered as the standard prerequisites for the program:

  • CS103 (Logic, Automata and Complexity)
  • CS109 or STAT116 or CME106 or MS&E220(Probability)
  • CS161 (Algorithmic Analysis)
  • CS107 (Computer Organization and Systems)
  • CS110 (Principles of Computer Systems)

I'm mentioning this since you only listed math classes.

In regards to research, if your neuroscience research was on the computational side, I think you'd be fine. IMO, I'd be more worried about the coursework preparation, since MS is mostly coursework based.

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I have the same GPA, no papers (one paper about computer vision in review), two A+ grades in graduate level Neural networks and Machine learning courses, and I haven't done basic computer engineering courses such as automata, OS or organization. 

I got rejected from Stanford MSc, UT Austin, and some others. I now realize that it was foolish for me to apply to those schools because of the lack of fundamental courses as well as the research experience. DO NOT only apply for the top. Your list is incredibly ambitious, if you can spend the money and have understanding referees, apply for these schools plus 3-4 less ambitious programs.

Also, note that the area you apply is the most popular area of research currently. Neuroscience has some parallels, but more mathematically involved (frankly harder) and does not exactly translate to the ML.

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