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I graduated this past May from UC Berkeley with a degree in applied math. I realized that I am very interested in getting a PhD in computer science. However, my programming experience is mostly self taught and I have only one introductory class in Python on my resume as programming experience. Right now, I'm working at a startup building risk models using machine learning. I do some coding at work, but not a lot. My primary interest is in AI (especially it's applications in video games) and my top schools are Stanford, Berkeley, USC, and Caltech.

I'm willing to spend the next few years building up a resume so that I can get into grad school, but the problem is that I don't know what to do. I can talk to my employers and see if I can get more work that involves programming. I could also work with them to publish our findings in academic papers. I can work on some projects on my own, such as building apps or something. Or I could take extension classes in CS. What would be the best course of action? Should I go for a masters instead? Does anyone who got into a PhD program without studying the subject in college have any stories to share? (Note: I have not yet taken the GRE).

As a bonus question, if you think another school besides the four I listed would be really great for AI, which one and why? And as an extra bonus question, does anyone know if it's harder to get into Berkeley as a grad student if you already went there for undergrad?

closed as off-topic by gman, Dirk, Massimo Ortolano, Brian Tompsett - 汤莱恩, Enthusiastic Engineer Oct 13 '16 at 20:46

This question appears to be off-topic. The users who voted to close gave these specific reasons:

  • ""Shopping" questions, which seek recommendations or lists of individual universities, academic programs, publishers, journals, research topics or similar as an answer or seek an assessment or comparison of such, are off-topic here. (See this discussion for more information.)" – Dirk, Brian Tompsett - 汤莱恩
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  • To answer your question about schools that have strong AI faculty: CMU, Georgia Tech, UT Austin, Cornell, UIUC, UW, and Michigan. It is a hot field so almost any top CS program will have good AI researchers. – Austin Henley Oct 13 '16 at 17:24
  • Pick a department. Read their program of studies. Read the prerequisites for the first year graduate courses you would take. Now work your way backwards until the courses you're looking at don't have any prerequisites that you don't feel you could skip over. Take those classes as a non-matriculated student. When you're ready to apply to your AI grad programs, you will present your Bachelor's and your transcripts of non-matriculated courses. Have fun! – aparente001 Oct 15 '16 at 4:10
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"Programming" is only one part of computer science, and arguably, the "easiest" part. The harder parts of computer science are the theoretical parts (e.g. math and machine learning), in which your background is strong.

To address your greatest concern, programming, my own experience is something like this: The easiest part of program is creating commands for things like "formatting." That is more tedious, than anything else. Certainly, Python or other programming experience is helpful in this regard, but is nothing that someone of your intellectual caliber should worry about.

A harder part of computer science is "logic," at least as expressed in flow charts. These include things like true-false "branching," or jump commands such as "goto," or loops and links. This part of computer science is harder than the formatting part, but not overly difficult.

The hardest part (for me at least) is mathematical concepts and equations. Once you've got the equations down, and can express them in "computer" form (using e.g., recursion), you are over the most difficult part. Related to this is machine learning, how the machine bootstraps itself through feedback loops.

So, relax. You have a good background in the hardest part of computer science. Naturally, you want to learn some of the "soft" stuff, e.g. programming, but until you get to the actual courses, what you don't know won't hurt you.

Besides the four California schools that you mentioned, I would consider Carnegie Mellon University in Pittsburgh, Pennsylvania. My father (Dr. Tung Au) retired from there as a professor 24 years ago, (and has a laboratory named after him). That school is known for robotics, artificial intelligence, and computer science. Another school you might consider is his alma mater, Illinois Institute of Technology.

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Kind of not an academic answer but lots of computer science is self-taught these days. If I remember correctly from when I taught there, Cal has access to databases like Safari and the like which will contain a lot of books about computer science and things like AI/Machine Learning/Whatever. Also great classes at MIT OCW and to a lesser extent online courses from Coursera and Khan Academy. Focus on C, C#, or Java, buy and internalize the Norvig and Russell textbook and build a few impressive applications and then with a math background that might be enough to get into a Ph.D. program. (And you'll need these skills to get into a Masters' program too.) If you have the money and desire to relocate I can highly recommend the MFADT at Parsons in New York, or the classes down at Stanford. Good luck!

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