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Fall 2018, MS in CS, GRE 322 (165 Q, 157V), TOEFL 114, GPA 8.85 VJTI,Mumbai (IT)
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ParthPanchmia Offline
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Fall 2018, MS in CS, GRE 322 (165 Q, 157V), TOEFL 114, GPA 8.85 VJTI,Mumbai (IT)
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Hey guys, need help for university shortlisting.

GRE: 322 (165Q 157V AWA 4)
TOEFL: 114 (29,29,26,30)
University: VJTI, Mumbai
CGPA: 8.85 (toppers: 9.3)

DMBS Project to automate the VJTI university admission and hostel software. Involved managing a lot of student, faculty data which I have twisted and written in my SOP to suit my profile for DS/ML.

Final Yr project is detecting duplicate questions in Quora. Aims at automating the software to detect duplicate questions using NLP and ML. Currently in development.

2 month internship at a startup as a role of a back-end developer. Again, not related to DS/ML but have tried to twist and write in my SOP.

Unfortunately no publications or research papers.

Attended Microsoft student partner workshops
Shortlisted in Transform Maharashtra for developing a solution to a universal problem faced my people in India.
10 MUNs attended including 2 CMUNs and was the Under-Secretary General of my school MUN (JMUN).

Recommendations.
Project Guide, VJTI
Associate Professor, VJTI
Head of Examintion Department, VJTI
All 3 are strong recommendations.

Looking for MS in CS and specialization as data science (or related courses like ML)

Some universities I shortlisted.

USC
UCLA
UCSD
GaTech
CMU
SDSU
UF
UCI
NCSU

Please evaluate my profile and suggest the ambitious, mod and safe universities plus some other universities that i may have missed and are good.

Also, I am re-taking my GRE in a bid to improve my quant score. Hypothetically, if i get a better score, say 327/328 with a 168+ in quant, will my amb mod safe universities change and if yes, which new and better ones could be added to the list?

Thanks a lot guys, would be really beneficial if someone replies.
(This post was last modified: 09-26-2017 07:44 PM by ParthPanchmia.)
09-05-2017 11:46 AM
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ParthPanchmia Offline
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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Tagging seniors for help
@Dragon_Warrior
@The_Observer
Edulix_Editor
@MSmaverick
@gurkanwals
(This post was last modified: 09-06-2017 05:36 PM by ParthPanchmia.)
09-05-2017 12:11 PM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)


Thanks
PROFILE EVALUATION GUIDE || PROFILE EVALUATORS
US university research page for CS specializations--> Click here
09-05-2017 04:07 PM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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USC - safe
UCLA - ambi
UCSD - ambi
GaTech - mod-ambi
CMU - ambi
SDSU - too safe, drop
UF - mod-ambi
UCI - mod
NCSU - mod

That's how I'd categorize them with your current test score. With a better one, your chances of getting in might go up, but not necessarily at all schools you're targeting. For example, at schools like UF and NCSU that have been known to prefer high academics over high test scores, getting high scores obviously helps, but it won't necessarily compensate for your GPA in that respect and "get you in".

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
09-05-2017 04:46 PM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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Thanks a lot The_Observer.
Are there any other good universities that I may be eligible for and have not listed?
I had another doubt regarding MS in CS with specialization as data science and MS in DS itself. What is the difference? Some universities have the 1st option while some have the 2nd. Secondly, people are saying to opt for MS in CS now and choose DS as an elective since MS in CS will be more diverse than MS in DS. What are your thoughts? If i decide to apply for both these courses mentioned above, will my SOP drastically change or will the gist regarding projects, courses, internships be the same?
I know I am bombarding you with a lot of questions but it would be really helpful if these doubts are cleared.
09-06-2017 05:18 PM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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"Are there any other good universities that I may be eligible for and have not listed?"

Well, of course, there are, but the definition of "good" in this context is very subjective. You need to define what "good" is for you (e.g. low costs of attendance, high availability of electives that you're interested in, etc) because what might be good for you might not necessarily be suitable for me or someone else. Unless you do some thinking on your part and come up with a list of priorities and constraints, no further shortlisting can or should be done. And I can't - and won't - help you there. Simple reason for that is the fact that Edulix isn't a counseling shop where we give applicants everything they ask for. Remember that all of us here are folks who have gone through the same steps you're doing, and we're better for it. We believe in giving applicants all the information they need to make a decision, and so we will be more than happy to guide you in the right direction. But you will have to ask yourself all sorts of questions and do a lot of introspection about your career goals and objectives. Go through university and program websites and learn the differences between the programs in terms of structure, formats, courses offered, etc, then ask for our opinions as to which one might suit your career goals the best, and request for a profile evaluation at that point.

"I had another doubt regarding MS in CS with specialization as data science and MS in DS itself. What is the difference?"

An MS in data science is very specialized, and as the name suggests, will train you to become a data scientist. Most DS MS programs will generally only have DS/statistics courses in it, with very minimal scope of branching out in other areas of study. On the other hand, an MS in CS prepares you for a more generic career as a CS person with the possibility of specializing in an area which may include data sciences. While an MS CS grad with a specialization in DS might not know some thing into as much detail as a MS DS grad, the CS grad is able to apply to and work as not just a data scientist, but also a database person or write code, etc., all of which a data scientist might not be able to do, depending on her background and skillset prior to the MS DS program. So in that sense, I'd prefer an MS in CS with a data science spec, because then you can apply to a wide variety of jobs down the line. See, although hiring managers don't necessarily care about the degree you did or its name, the sad truth is that the initial culling for any job is done by HR people who might not know what to make of someone with a data science degree applying for a hardcore CS job when almost every other applicant to that degree has a CS degree. In such a scenario, your resume might be dropped just because of ignorance and bad luck, and I'm not saying this will always happen but it might, at least until DS programs are more popular. And even then, if a job needs skills that you could've picked up in a CS program but you didn't because you did an MS DS, you might end up wishing you had done that instead. Specializing further in one field, say DS, is comparatively easier down the line from a more generic path, rather than the opposite, once you're pigeonholed into one thing because your first job or first few jobs were all in one domain because you have a very specialized degree.

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
09-06-2017 06:26 PM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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The_Observer
Sorry for not researching the universities and asking you you to list them for me. My intention was to just be on the safer side since the ones I selected were all mostly amb and some mod. Hence wanted your opinion for more mod and safe universities. Anyways, as you said, Ill research it myself.

The reply about MS in CS and MS in DS was very helpful. Is it easier to get an admit to MS in DS than MS in CS? If thats the case, Ill have to still ponder but if its not, going for MS in CS will be a no-brainer.
09-06-2017 06:59 PM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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"Is it easier to get an admit to MS in DS than MS in CS?"

Not necessarily. For example, NCSU has an MS in analytics that is pretty similar to many other data sciences programs, and it is more competitive than the MS CS program. In other universities, the reverse might be the case. It all depends on how the program is structured, what kind of profiles the program is looking to attract, what sort of applicants it gets in terms of GRE score averages, academics, work-ex, and all those things are qualitatively and quantitatively looked at. Also, since application evaluations are done pretty holistically by most (if not all) universities, someone with more "technical" CS work-ex or research experience might find it a little easier to get into a traditional CS program as compared to a DS one. But that doesn't need to be case, because again, holistically if a person with a solid CS background has good data science/analytics/statistics experience, they might find it easier to get into a DS program or a MS CS with a declared DS specialization (more on this later in this post). Whether any person gets into a program or not is highly dependent also on the quantitative and qualitative suitability of the competition in the applicant pool for a given intake. If you're applying for an MS DS program with little or no DS/analytics/statistics experience, and most other applicants are from similar backgrounds with little DS experience too, then you might have decent chances to get in just because you're at-par with respect to the competition. But for any program, if the competition from the applicant pool for a given intake is such that there are other people who have more relevant skills and experience, then your chances might diminish just because your competitors are more suitable for that program than you are, either qualitatively or quantitatively - unless you can convince the admissions committee that you're suitable too, mainly from your SOP.

Which brings me to my next point: the SOP is essential in an application, and a part that's very often unfortunately misunderstood and underestimated by applicants. The SOP is the place where you get to tell the program admissions committee about things that aren't apparent in your profile from your CV and recommendations. This is the place where you're supposed to mainly convey to the AdCom two things: why is the program suitable for you, and why are you a suitable candidate for that specific program. That's how you can convince that you have the right set of background and skills, even though you're applying for an MS in DS (for example) with minimal formal coursework and/or work experience with statistics/analytics/data sciences, but if you've taken MOOCs dealing with those topics. As such, because you have to convince each program's AdCom as to your suitability for that specific program, your SOP has to be different for each program you apply to. Recycling SOPs is a cardinal sin and possibly one of the top three mistakes you can do in an application (along with selecting the wrong recommenders and intentionally hiding undesirable things from your applications). I hope that answers your earlier SOP-related query. For more info on SOPs and how to make an effective one, go through the "Elements of a good SOP" thread here on Edulix that's in the "Broad topics in Academia" forum.

EDIT: What I meant by "holistically if a person with a solid CS background has good data science/analytics/statistics experience, they might find it easier to get into a DS program or a MS CS with a declared DS specialization (more on this later in this post)" was this: someone who has some statistics/analytics/DS work-ex is better-off than someone who has none. Someone with a CS background (in general) is probably better-off for any MS in CS program, generally speaking, as compared to a humanities major, especially if they didn't have a CS-heavy courseload in their UG degree or CS-related work-ex. So, as far as I can think of this, the pecking order for a MS CS program with a specialization in DS might be as follows (and keep in mind that this is a very simplistic example, and an example alone): at the top are people who have relevant work-ex and academics, who are able to convincingly explain in their SOP why the program is a good fit for them in terms of their career goals, and why they're a good fit for the program with their skills and experience. Next up are folks who might not have had a lot of formal coursework in their expressed area(s) of interest in their SOP - which is what I meant by "declared specialization" - but those who can still convince the AdCom that they're a good fit, either because they have work-ex in related fields or because they've taken MOOCs or something like that. After that are the folks who have neither a lot of relevant coursework, nor a lot of work-ex in an area relevant to their declared specialization in their SOP, but still their SOP highlights their accomplishments and interest enough, and is backed up by an affirmation of their potential to succeed in their LORs, that the AdCom might want to give them a shot. The last up are folks who have very less work (either through courses taken in the past, MOOCs, or work-ex) that's relevant to their declared specialization in the SOP, and those whose SOPs aren't convincing enough or very generic and/or cliched. Remember, that an SOP at the graduate level always needs to be very focused, and you have to mention 1-2 specializations in it, why you're interested in them, and how your past experiences and skills align with them. Unless those things are highlighted in your SOP, it won't be convincing enough, and you will be rejected, especially if you have no other redeeming factors in your favor (such as the presence of very relevant work-ex or research experience which might give the AdCom an implicit insight into your potential to succeed in your specific concentration/declared specialization area even though you might not have mentioned the suitability outright). That's why relevant coursework taken in the past or work-ex is always very valuable - given you're able to relate it to your declared specialization during your MS and your post-MS short-term and long-term goals in your SOP.

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
(This post was last modified: 09-07-2017 08:27 AM by The_Observer.)
09-06-2017 08:32 PM
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Post: #9
RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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GRE: 322 (165Q 157V AWA 4)
TOEFL: yet to give but expecting 100+
University: VJTI, Mumbai
CGPA: 8.85 (toppers: 9.3)

2-3 minor projects in web development and machine learning.
1 major project which involved automating all the activities in the VJTI hostel. (currently being deployed in the college).

2 month internship at a startup as a role of a back-end developer

Attended Microsoft student partner workshops
Shortlisted in Transform Maharashtra for developing a solution to a universal problem faced my people in India.
10 MUNs attended including 2 CMUNs and was the Under-Secretary General of my school MUN (JMUN).

Good overall profile. There is lack of research work, and there is nothing much that can be done at this point in time.


Recommendations.
Project Guide, VJTI
Associate Professor, VJTI
Head of Examintion Department, VJTI
All 3 are strong recommendations.

Its good that all are strong, but you might consider having 2 acad and 1 industry LOR. Universities are acad institutions, and they value your Prof's views more than they would generally value industry people

Looking for MS in CS and specialization as data science (or related courses like ML)

Some universities I shortlisted.

USC A
UCLA A+
UCSD A+
GaTech A++
CMU A++
SDSU No idea
UF No idea
UCI M+/A
NCSU M


Please evaluate my profile and suggest the ambitious, mod and safe universities plus some other universities that i may have missed and are good.

UMN M+/A
UPenn A


Also, I am re-taking my GRE in a bid to improve my quant score. Hypothetically, if i get a better score, say 327/328 with a 168+ in quant, will my amb mod safe universities change and if yes, which new and better ones could be added to the list?

My evaluation will not be affected unless you score >=169 in quant. In that case NCSU goes to S+/M. Nothing else changes.

Gurkanwal's Infobank
MS in CS [ML/DS] Fall 2017!
UCSD| UMass | UPenn | UMN | NCSU | CU-Boulder | UTA | CMU | UCLA | Gatech | U. Waterloo

My own profile evaluation
General Suggestions
+Rep if the post helped!
It's not the size of the dog in the fight, it's the size of the fight in the dog. - Mark Twain
09-07-2017 11:56 PM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), GPA 8.85 VJTI,Mumbai (IT)
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VMEHTA Here is my profile.
09-15-2017 10:00 AM
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RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), TOEFL 114, GPA 8.85 VJTI,Mumbai (IT)
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I have updated my profile by adding my TOEFL scores and writing a short descriptions of my major projects. Apart from the universities mentioned above, can you please evaluate these new ones as well.

For MS in CS in ML/DS
NEU
ASU
TAMU
UPenn
SJSU
UMP
NYU
UMCP
University of Toronto
University of Waterloo
University of Alberta

For MS in DS
CMU (MCDS)

For MS in IM
UIUC
UW

The_Observer
Edulix_Editor
Chirantar
(This post was last modified: 09-27-2017 06:02 PM by ParthPanchmia.)
09-26-2017 07:50 PM
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Post: #12
RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), TOEFL 114, GPA 8.85 VJTI,Mumbai (IT)
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NEU - safe
ASU - safe
TAMU - drop
UPenn - ambi-mod
SJSU - safe
UMP - Which one is this?
NYU - mod-ambi
UMCP - ambi

For MS in DS
CMU (MCDS) - ambi

For MS in IM
UIUC - mod
UW - ambi

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
09-27-2017 01:03 AM
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Post: #13
RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), TOEFL 114, GPA 8.85 VJTI,Mumbai (IT)
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(09-27-2017 01:03 AM)The_Observer Wrote:  NEU - safe
ASU - safe
TAMU - drop
UPenn - ambi-mod
SJSU - safe
UMP - Which one is this?
NYU - mod-ambi
UMCP - ambi

For MS in DS
CMU (MCDS) - ambi

For MS in IM
UIUC - mod
UW - ambi

Sorry it was UMN and not UMP
Any particular reason why I should drop TAMU?
And what about the universities of Canada which I mentioned?

Thanks for the evaluation.
The_Observer
09-27-2017 12:05 PM
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Post: #14
RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), TOEFL 114, GPA 8.85 VJTI,Mumbai (IT)
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(09-26-2017 07:50 PM)ParthPanchmia Wrote:  I have updated my profile by adding my TOEFL scores and writing a short descriptions of my major projects. Apart from the universities mentioned above, can you please evaluate these new ones as well.

For MS in CS in ML/DS
NEU
ASU
TAMU
UPenn
SJSU
UMP
NYU
UMCP
University of Toronto
University of Waterloo
University of Alberta

For MS in DS
CMU (MCDS)

For MS in IM
UIUC
UW

@[The_Observer]
@[Edulix_Editor]
@[Chirantar]
Good profile and CGPA. I will evaluate for MS in CS as follows.

USA

For MS in CS in ML/DS
NEU Safe
ASU Safe
TAMU Highly Ambitious due to absence of research profile, I will recommend to apply to Purdue
UPenn Ambitious
SJSU Safe
UMN Moderately Ambitious
NYU Ambitious
UMCP Ambitious

Canada

University of Toronto:- Super Ambitious, huge competition for precious 6-10 seats in CS department and requires heavy research profile.

University of Waterloo:- Ambitious Contact the professor mentioning area where you wish to do research/work, if professors likes your study proposal then prof/guide will suggest you to formally apply and your application will be eventually in strong position while selecting candidates as it totally depends on professors.

University of Alberta:- Ambitious. Again follow the same process which i said above.


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TUM | TUB | Chalmers | KTH | Western Ontario
Destination: TUM
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if my post helps
09-27-2017 08:29 PM
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The_Observer Away
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Posts: 17,841
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Post: #15
RE: Fall 2018, MS in CS, GRE 322 (165 Q, 157V), TOEFL 114, GPA 8.85 VJTI,Mumbai (IT)
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Reason to drop TAMU being exactly what Chirantar has said. If you want ambitious options: Duke, Vanderbilt, Wisconsin. I'd drop Toronto and probably Waterloo as well.

1) Please mention as many details as possible about your academics, research and work-ex, in terms of projects worked on, technologies used, roles/responsibilities handled, papers published/presented, awards/honors obtained, etc. All those have to be put in the misc details section of your UniSearch profile if you expect any help on Edulix. Also, before requesting for profile evaluations, please go through this excellent post.

2) Please take some time out to read these three threads in their entirety. PLEASE do that before asking questions about universities from a comparison perspective, or jobs, or coursework, or H-1B visas, or "placements", irrespective of which univ/department/program/major you're applying to.

I love to read, and then I regurgitate. I write - a lot - as my posts here and on other outlets would show. I do not make apologies for what I write (and how long it is). I do not sugarcoat things either. I don't tolerate vague questions, for any reasons - ignorance arising out of an inability to locate information when the necessary tools to do so (i.e. the internet, libraries, university websites, other forums/bulletin boards, etc.) are readily available, is not any kind of an acceptable excuse.

"Don't be daft." - Ancalagon The Black

"With the exchange rate where it is now, it should be a strong deterrent against picking a slightly better program for a lot more tuition fees." - coolguru
09-27-2017 09:34 PM
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