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UCLA vs UCSD MS Computer Science


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Hi guys,

I just got the offers from UCLA and UCSD for MS in Computer Science major. I am interested in distributed systems/computer vision/deep learning, but planning to explore various fields. Both are the great programs, but it's so hard to make a decision, and I need some help. So far, I think the pros and cons of each school are

Pro:  Research Oriented (perhaps more open to masters students?)
          Seems like there are more TA opportunities
Con: I think recently they expanded the size of the program, and last year they admitted 701 masters students (too many students?)

Pro:  Overall Reputation for UCLA is really strong (advantage for job hunting?)
          More startups nearby
Con: There aren't many classes related to computer vision/deep learning/etc

It feels like both CS department is really strong, but the difference is that UCLA CS department is traditionally prestigious but less active these days while UCSD CSE is relatively young but dynamic. Please correct me if I am wrong. If you know some more information or experience with these programs, please help. Also,  Does anyone know how difficult to transfer to the internal Ph.D. program in the course of MS program for each school?
Thanks in advance!

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