thedreamykind

I'd hoped this wouldn't happen, but since I've accepted admission and put down my papers I've basically been doing nothing. I'm horribly unproductive at work, and I've been making zero progress on my personal projects as well. I feel a little better knowing I'm not the only one .

Thank you PhDerp, I've started looking forward to it now . I'm not looking forward to the roommate finding and house hunting though. Good luck at USC!

PP1: 165V/170Q PP2: 167V/169Q GRE: 170V/168Q I gave some tests from The Princeton Review as well - I don't remember my exact scores, but they were in the 165-170 range for Q, and 155-162 range for V. I think the PowerPrep tests are pretty accurate indicators of actual test performance, and it would be best to save them for the last few days before the test.

I'd have gone to Columbia, or UPenn (if it was much cheaper than Columbia). Depends on what you want to study - the MS CS curriculum would likely be fairly different from SE at CMU. From my understanding, the SE course is coursework oriented - complete your credits, get a job and leave. Also, the courses would probably be tailored to SE rather than core CS. MS Computer Science, on the other hand, would give you more exposure to core Computer Science (algorithms, machine learning, NLP - whatever you're interested in), and also more research opportunities if you're looking for those. Also, while the CMU brand name does stand out, you can't just go by the rankings. CMU has around 8-10 different masters courses related to CS, and courses like MS CS, Language Technologies, Machine Learning, etc are very difficult to get into. MS Computer Science at Columbia is their main CS course. In terms of internships and jobs, I don't think you'd have trouble finding opportunities at any of the top-20 schools. Columbia, being in NY, will have easy access to the financial industry (which has plenty of tech jobs, I'm working one right now), and also the start-up scene in NY, which I've heard good things about. Congratulations on your admits, and good luck with your decision!

Thanks everyone for your inputs. Keeping everything in mind, I have accepted the offer from UT Austin. Though I was sad to give up Wisconsin, it had to be done .

Hi. Most universities don't require you to convert your CGPA to the 4-point scale - they let you fill out your original GPA and ask for the maximum. If it is mandatory, you can consider WES grade conversion (google it). Or just scale it to 4.0 and send your transcripts, that's what I did for one of my applications (Columbia, I think).

Glad you found it useful, good luck for your test!

I decided against Georgia Tech because I was told that they have larger class sizes than the others I'm considering, making it much more difficult to find funding opportunities. Also, they mandate 4 courses per semester, and I'm not too keen on that either. Would you mind giving me your reasons for why you would've chosen it?

Hmm, interesting. The general impression I've been getting is that historically, funding has not at all been hard to find, at least in the Computer Sciences department. Things may have changed this year - I'm not sure if their intake is any higher than usual..

Thanks for your reply newgrad2014. Like you said, it's easier to get TA/RA appointments (with tuition waiver) at Madison. It's not that hard to get some opportunities at Austin, though most of them lead to in-state tuition rather than a full waiver. Considering the tuition cost difference (Austin is around $4000 per semester cheaper), tuition is not the deciding factor for me. I was trying to determine if one deparment is any better than the other, but everything suggests that they're equally good. I'm interested in Machine Learning / NLP, and there's nothing to indicate that the ongoing research is better at either place. I'm scared of the weather in Wisconsin (not used to extreme cold), so I may end up choosing based on that .

Hi All, I've narrowed down my choices to these two, for MS Computer Science. I'm interested in Machine Learning / NLP, but this may change based on what kind of exposure I get once I start grad school. Based on the information I've been able to gather, I see these as the pros of each - UT-Austin Cheaper tuition Better weather (I'm from India, and not used to extreme cold) Better internship/job opportunities (but shouldn't be a problem from Wisconsin either) Live music UW-Madison Has a reputation as a research school. No differentiation between MS and PhD applicants. Easier to get TA/RA appointments. Smaller intake? So far I've been unable to decide between the two. Any pointers would be appreciated. Thanks! PS - Mods, I've also posted this in the April 15th forum, but this looks like a better place. Let me know if you want me to delete either post.

I gave my GRE on August 20, 2013 and managed to score pretty well (168Q, 170V, 5.0 AWA). I don't remember too much now, but I wrote an email to a friend detailing my experience and giving some preparation tips. I thought I'd post it here as it may help other people. Here goes. (I mostly talk about verbal, because maths is pretty manageable for most people) So, words. I'll briefly walk you through the experience I had. I went to The Princeton Review for classes. The classes were somewhat useful (not too much), but I don't think I scored more than ~162 in English on any of their tests (I took 3 or 4). While I wasn't dedicating proper time to preparation, I expected to get better over time. I took a week off from work, before my exam, to prepare. Given the limited time I had, I didn't really do huge word lists. Based on the research I did, I tried to focus on the official ETS prep material. The first PowerPrep test I gave, I scored 165 - this was a huge confidence boost. The difference between the real questions and the ones asked by Princeton, Manhattan etc became apparent - ETS focuses a lot more on complex passages which take time to grasp, but not so much on difficult and obscure words. I spent time analyzing my test and learning the words they used that I didn't know. I did this for all their tests (2 in the official guide, 2 on PowerPrep) and also the practice question sets they had. This really helped, and my performance was more or less consistent on all their tests. Based on the amount of time you have, I would say don't necessarily go for the longer word lists. And the words you do learn, try to learn them "in context" - how they're used in sentences. For me, words are very difficult to remember with just their meanings, but much simpler if I associate them with an idea or a memorable sentence. An example (I don't remember where I picked this up) - Ostentatious is a "flashy word for flashy" . I don't know if you've come across the Magoosh blog - but they have some very good articles and reviews of prep materials. Here are some resources you may find useful - A high frequency word list I studied - link Magoosh's vocabulary PDF, quite useful - link Magoosh's advice on word lists, quite useful - link One month study schedule - link - you can browse through this and come up with your own strategy. I used their one week guide and customized it to my needs. Some general advice - Read the official guide, it's more useful than you might think. After all, it's from the people who make the test. For essays, you don't need anything other than reading their guidelines, scoring guide (they clearly tell you what they expect), and the sample essays they've given. For maths, you don't need anything other than browsing through the "math review" chapters they have, they cover everything they ask. I would also say this - try to time yourself and do sets of questions rather than spending time randomly practicing. You'll get a much better idea of your strengths and weaknesses. And verbal - spend time practicing a lot of RCs, and try to get used to complex/confusing passages. I could barely get through my verbal sections in time. Feel free to ask me any questions, I'll reply if possible. Good luck!

Hi All, I've narrowed down my choices to these two, for MS Computer Science. I'm interested in Machine Learning / NLP, but this may change based on what kind of exposure I get once I start grad school. Based on the information I've been able to gather, I see these as the pros of each - UT-Austin Cheaper tuition Better weather (I'm from India, and not used to extreme cold) Better internship/job opportunities (but shouldn't be a problem from Wisconsin either) Live music UW-Madison Has a reputation as a research school. No differentiation between MS and PhD applicants. Easier to get TA/RA appointments. Smaller intake? So far I've been unable to decide between the two. Any pointers would be appreciated. Thanks!