compiler_guy

With relevant work experience and good LOR's, you should consider ALL schools(even Stanford). Good luck!

Quant score is not good. Probably consider schools that are ranked 20 and onwards: http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-science-schools/computer-science-rankings

The chances are always slim, so applying to more schools as a sort of investment. But the good news is that applying to more schools increases your chances! Other possible schools to consider: Virginia Tech, Georgia Tech, University of California (LA,San Diego,Irvine etc,.), U Wisconsin Madison, U Colorado Boulder and possible a few more With relevant work experience and letters of recommendation, you have a more than decent chance to get in to the Masters program!

You might want to consider to apply to more universities (11-14). Just base on chance alone there is a 5-10% chance of getting to an average top-30 university, and this chance drops to around 3% for 3-4 of the universities on your list.

Some programs will not even look at your application if your GRE scores do not pass a certain threshold. 1. Yes, in most of the applications. 2. It all depends on the program and university policies. 3. Looks good, but be sure to aim at programs that have research that fits your interests and experience.

Programming languages is a great option, but don't confuse it with programming - that is usually the least significant part. It is more about the theory of programming languages, how to verify programs, correctly synchronize threads, etc..

It depends on the program. Different departments at different universities have different pre-reqs. You might want to visit the website of each program and check out the requirements.

A good place to start is the CS graduate school ranking: http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-science-schools/computer-science-rankings Other than that, I suggest you only go to a program which have classes and maybe research projects that fits your interests (Machine Learning, Systems, Computer Graphics and so on...)

V 140 is very bad, and might derail your chances. Q 167+ and A\W 4 are awesome. I suggest you send both gre scores if you can, and just write the upper most mark you got. If that is not possible in the application form, make a judgement call depending on the average GRE thresholds of the program you are applying to. Try to apply to a number of universities that are spread out differently by rank to maximize your chances. Good luck.

If you have extra money to spare, and you are not in a hurry to get your PhD, yes your plan will work. However, be sure to aim at master programs that have research opportunities for master students.

I haven't studied in either of these institution or lived in either cities, but I Cornell is better ranked for Computer Science. Regarding bullets 2, and 3 - you could ask the graduate program coordinators, they probably have the most up-to-date information. Linkedin search is also valuable.

You probably should consider schools other than UCs, such as Cal State U schools and even better - schools outside your state. If you want to focus on some specific research field for your masters, that may help your chances (like graphics, AI, systems and such). Ranking: http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-science-schools/computer-science-rankings Good luck!

What is the quantitative, vocab and writing part of gre? either way it depends on your letters of recommendation.

BTW, I think most Canadian universities offer funding for MS students in CS. You should check that out...

I think U Wisconsin Madison offers MS funding in CS. But you would need to check their website just to be sure

What kind of research topic are you interested in? Choosing universities by research topic is probably a better way to get in, because then there is some fit between you and your POI. So there might be a awesome POI in a lower ranked university, and you would prefer working with him. That would be better than just picking universities by their ranking. Ranking is important, but you don't want to get stuck in a high ranked university with no POI to work with.

Good luck to you too! I might want to apply to as many universities that could fit your interests, even universities that are not the top 25. Also it is always a good idea to contact POI in those universities to check if their current research is related to something you want to do (because sometimes professors don't update their website's that often, and their research might change according to funding and stuff).

Probably not, 167 is good enough. LOR's are more important...

Depends on quality and authors of the letters of recommendation

GRE is mostly to meet the cut-off (so if you score below the cut-off, the committee would not even look at your application). If you want to maximize your chances, you might want to apply to at least 5 more universities, since the chance of getting admitted is relatively low (programs admit between 3% to 10% of applicants).

You could send the scores right now, I don't see any reason why not. However, some university departments will not process your GRE score if you didn't submit your PhD application, they usually say so on their website. So better finish the application first, then send the GRE score.

A good place to start is: http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-science-schools/artificial-intelligence-rankings and http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-science-schools/computer-science-rankings Other than that, AI is a very large field so you probably would like to narrow down your interests to a specific sub-field or fields in order to refine your search.

90 to 120 days from the application deadline. Also in the winter semester it is usually harder to get in.

Usually, no. For sure not at the proportion of the people applying. Departments usually want to keep a balanced faculty across a wide range of interests,

Machine Learning is a very large area, with lots of sub-fields. So perhaps you might want to focus your question on the particular sub-fields that interest you, and then find the relevant professors.