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Found 82 results

  1. I'm new here, so I apologize if I ask too many questions! Basically, I'm currently a senior at NYU and in May I'll be graduating with a B.A. in Math and Psychology. Going into my senior year, I had been planning on applying to several Ph.D. programs in Data Science and Statistics and my career goal was to be a data scientist. However, upon meeting with the professor whose lab I do research in, he stated that it would be very difficult for me to get into any Ph.D. program with only a year of undergraduate research experience. So, I applied to 6 Masters programs and the Ph.D. in Data Science program at NYU (this has been my top choice since sophomore year so no way I wasn't going to give it a shot!). Fast forward to now, I made it up to the interview for the Ph.D. program, but yesterday I got an email saying I was offered admission into the Master's program in the Center for Data Science, and that I am not eligible for any scholarships. I have also been admitted to the Master's of Engineering in Computer Science program at Cornell Tech, as well as a couple of other M.S. programs at NYU, and I'm waiting to hear back from the three other programs. Here's where my questions come up. As I think about it more and more, the program at Cornell Tech becomes more appealing. For one thing, I think it's a more versatile degree. They have data science courses I could take, and with the degree itself I'd be a candidate for software engineer positions. As such, after completing the degree I'd likely be able to go down either route, albeit the data science route would be a bit tougher with this degree than with the M.S. in Data Science. However, I've also found jobs in software engineering to be more appealing lately. I think around my junior year of college I started to realize a software engineer career seemed like a good fit for my interests, but by that point I thought it was too late in the game to switch routes unless I got another Bachelor's in Comp Sci - who knew! Also, I've been completely lost at where to look for scholarships. I applied to one that Cornell Tech sent out the application to, but I haven't received any merit scholarships from the programs I've been admitted to. That being said, even without scholarships, the Cornell Tech degree would be approximately $8,000 less right off the bat. Additionally, it's a one year program, as opposed to the one at NYU which is a two year program. Is it presumptuous of me to think it'd be reasonable to take out $40-50k in loans, with the expectation that with the Computer Science engineering degree I'll likely be able to make decent money as a software engineer in NYC not long after graduating next spring? If it helps, I'll be graduating from undergrad with about $10,500 in loans, and if I do get a well-paying job after grad school my plan is to live as if I'm making $40k a year until my loans are paid off. I'm the first in my family to go to college, let alone grad school, so any advice is greatly appreciated! I've heard that some companies will pay for you to get a M.Eng., but honestly at this point I'd rather get the degree first since I don't think I'm qualified for many tech jobs currently. As a recap, my two main questions are: 1. Is it a smart decision to do a Master of Engineering in C.S. at Cornell Tech when I'm open to becoming either a software engineer or data scientist? 2. Is it reasonable to assume I'll be able to get a decent job with a M.Eng. degree in C.S. and that I'd be able to pay of ~$60k in loans in a reasonable amount of time? Thank you!
  2. (Please consider scrolling to the bottom for some of my concerns. I suffer from anxiety and I know I'm needlessly stressed, but any pointers are immensely helpful.) Student Type: International Asian (Brown) Female Undergrad: Small university known in academic circles Major: Computer Science (might complete my math minor next sem) GPA: 3.91/4.0 (Major GPA 3.94/4) Relevant Courses: Calc 1, Multivariable Calculus (2&3 combined), Linear Algebra, Probability & Stats, Intro to ML, Advanced ML, independent study (somewhat of a research project, basically assisting a professor) focused on ML. A's in all except calc 1. I'll be completing a Capstone Project in privacy-preserving ML and an intensive math course on data science in the fall and a stat inference course in the Spring. A's in all other CS/math courses except for 2 systems courses. GRE: Taking it next month, hoping for a 166+ in Q, 160+ V Research: The independent study project I assisted on would have resulted in a paper but COVID delayed things terribly. I'm going to continue some work on it if possible over the next few months maybe send it to a conference. If I contribute to the literature during the capstone project I get to convert it into a thesis the sem after that, hopefully get it published (though I doubt that as of now) Work Experience/ Projects: 3 coursework projects using deep learning (are coursework projects given any emphasis?) Data viz/ analysis intern briefly at a GIS lab Data analysis intern in the marketing division of an investment firm/bank Couldn't intern this summer so personally working on mini-projects to integrate prescriptive analytics/ operations research concepts into the DS pipeline (do personal projects matter? I know they help for jobs but not sure about masters) Not too relevant but also: TA for 2 semesters (maybe 3), interned at a consulting firm and was in charge for all the data collection/ scraping for a project with basic analysis using Excel Letters of Recommendation: 2 (hopefully) strong who I've known well and worked with extensively (one of them was a professor at a top 5 CS school in the US), 1 moderate-strong who will write good things but I haven't worked with them as much Possible programs: MS Data Science; MS Analytics (only those with freedom to take computation-heavy courses); MS CS with a concentration/ specialization in ML (course/project based not research based, or professional programs) (I think I should crosspost this in CS?) Possible (REACH) schools I may apply to (not all): UPenn (MSE DS), CMU (MCDS), Northeastern (MSDS); professional masters in CS with ML track programs perhaps at UIUC, UW Madison, UCI, UToronto (MScAC), Cornell MEng; Georgia Tech (MS Analytics) Concerns: I know I have good stats and can get my foot in the door but I'm worried because I don't have significant work experience which seems to be important for some DS/ Analytics/ professional MS programs. Though I do have experience with DS related stuff (I decided early I wanted to get into it), I don't have "proper" research experience/ papers either, which seems to be a hurdle for traditional MS programs, even if course-based. I don't know what to emphasize besides some coursework projects and some limited experience outside school. I am confused where I have a better chance - DS/Analytics or CS, which is why programs with a good mix like Penn or CMU are super appealing. Need suggestions for: Finding good safety/ moderate range options, either for professional/course-based MSCS with ML, or MSDS with computation heavy courses/ freedom to take electives. There are plenty of good analytics options but given that I have studied CS and even ML, paying $5k+ to take intro courses isn't too appealing (one exception is the GaTech course that has business courses alongside a computational track). For example, UW MSDS and Columbia MSDS have lots of stuff I've already studied. On contacting Northwestern's MSiA program they said they may or may not waive the Intro to Python/Java requirement, which is ridiculous. Freedom to take electives would be great. I am open to Canada as well, though I'm not sure yet. Also - I am somewhat concerned with brand names because I may move elsewhere after the STEM OPT visa, though it isn't a top priority. If you know about programs in the UC system that fit and are within reach, those might give me the best brand/quality/buck ratio, besides GaTech, though I would prefer being in California. I am interested in getting into the industry but I'm not restricting myself to just tech, retail/marketing/consulting with good DS departments would be fun too, so some business courses are also welcome though not a dealbreaker. Freedom to take electives from Industrial Eng/OR/MS would be nice.
  3. Hello! I'm currently a rising sophomore with a tentative goal to do graduate studies in Statistics or Data Science. I was wondering what pure/applied math or stats upper division courses you would recommend that would give me a firm foundation? Here is the math course browser: https://www.ucsd.edu/catalog/courses/MATH.html I was thinking about taking one of the Algebra classes with Intro to Numerical Analysis, but I am not sure. Thanks in advance!
  4. Hi everyone! First time posting here. I was looking for some feedback on my profile and what kind of universities I should be targeting. I'm not looking for a PhD, want to gain better knowledge of Data Science to improve my career prospects. Looking for universities in both US and UK. Degree: B.E. (Hons.), Electronics & Instrumentation Engineering, BITS Pilani Goa (Tier 1 university in India), CGPA: 7.8/10 GRE General: 336 (Q 170, V 166, AWA 4.5) Had taken the TOEFL in 2018, will need to take it again this year. Score last time around: 112 (W:29 R:29 L:29 S:25) Grades in Relevant courses, converted to US equivalents: Mathematics - I (Linear Algebra & Geometry): A, Probability & Statistics: B, Mathematics - II (Calculus): B+, Mathematics-III (calculus): B- Work Experience: 3 years so far as a data scientist (2 years in an analytics consulting firm, 1 year at a startup working with a sports franchise - this is the area I would like to proceed with). Another year before I go. Research Experience: None LOR: a professor I had a project under in college, my manager at the consulting firm and my current boss (CEO of the startup). I'm open to consider any programs in the US or the UK. Thanks!
  5. Hello everyone! So I've been accepted into both schools online Data Science/Data Analytics Engineering programs. I'm having a difficult time deciding which to pick. My end goal is to move into a PhD program in computational neuroscience/cognitive psychology upon completing the program. I didn't expect to get accepted into UVA so once I got GMU's acceptance I accepted and was registered for my first class so if I decide to switch programs it would be a bit of process. A few points to consider: - UVA's program will leave me with double the out-of-pocket(~14.5k vs 7.3k) cost even after my current employers generous tuition reimbursement (10k per calendar year). - GMU has a start date of June 1st and UVA is for Fall 2020. - Both programs would have the same graduation date of Spring '22 despite staggered start times - UVA offers two machine learning classes while GMU does not - UVA's curriculum only allows for two electives but GMU's allows for half your course load to be elective I guess I'm kind of caught up on the out of pocket cost to justify making the switch but in the end I want to make the best decision for my future academic goals. Thanks for reading!
  6. I can't seem to find much about people applying to data science and analytics masters programs so I thought I'd start one myself. I'm super frustrating with not being able to find information on when decisions will be sent out, so I'm hoping find out if anyone has heard from anywhere. I've applied to: Chicago's MA in Computational Social Science Chicago's Masters in Analytics Georgetown's Masters in Analytics (focus in data science) Northwestern's MS in Analytics LSE Applied Social Data Science and Data Science masters programs I just found out yesterday that I've been accepted to UVAs masters in Data Science. Has anyone heard back from any of these schools??? Just for reference... School: Hillsdale College Major: Psychology and Political Economy, minors in French and Mathematics GPA: 3.53 (4.0) psychology major 3.90 (4.0) GRE: 162 (81%) Q, 165 (96%), 4.5 AW Relevant Courses: Statistics for the Social Sciences, Econometrics, Linear Algebra, Multivariable Calculus, Mathematical Statistics, Statistical Learning Other things: As far as programming I have experience with R and SPSS and have basic knowledge of HTML, C++, and SQL. I'm in the process of publishing psychology research as first author, have leadership experience in my sorority and two other campus organizations, have been my psychology department's statistics and SPSS tutor since sophomore year, am part of both the psychology and economics honoraries, and spent a month at Oxford this summer taking two courses.
  7. Hi, I did my engineering in electronics and have 3 years of work-ex as a data scientist. I'm interested in working as a data scientist in a social impact firm upon graduating and I'm quite confused between the mentioned programs. I have received 50% scholarship from both programs at UChicago and none from NYU. Any insights into any of these programs would be greatly appreciated!
  8. Hi everyone, I'm confused between two programs - 1. MS in Data Science at NYU CDS (No aid, $80k tuition for 2 years) 2. MS in Computational Analysis and Public Policy at the University of Chicago. ($40k aid, $60k tuition for 2 years) As an international student with background in data science in the tech industry, I'm keen on working as a data scientist in social impact firms. Understandably such jobs are rare in the US and I'm concerned about the financial aspects of repaying the loan. The NYU degree will help me land a well-paying job after graduation using which I can pay off my loans. However, policy is a field on interest to me and I would like to study the same at Harris. Any advice would be much appreciated.
  9. Hi everyone, I am an international student accepted to these two programs for Fall 2020. I am struggling to decide which one to go. 1. Georgetown's MS in Data Science and Analytics program (no financial aid, $70k total for 1.5 years) 2. UChicago's MA in Computational Social Science program (interdisciplinary focus) (2/3 financial aid, $40k total after aid for 2 years). My goal after graduation is to find a data scientist position in consulting/tech industry. I plan to work for a few years in the U.S. first, and then apply to PhD in social science (business, public policy) down the road. (I am interested in the research of the social causes and impact of innovation in the private tech sector). Reason for Georgetown: 1. A data science masters degree will lead to higher income and better job prospect than an MA in Computational Social Science. 2. I currently work in D.C. and have established network here. I personally like D.C. more than Chicago. And the job market at D.C. will be better than the market at Chicago. Reason for UChicago: 1. cheaper tuition ($40k for 2 years vs $70k for 1.5 year) 2. My long term goal is to pursue a Ph.D. in social science, hence MA in Computational Social Science is more relevant in the long run. 3. the teaching quality at the program in UChicago will be significantly higher than that at Georgetown. (1/3 of courses at DS program at Georgetown are taught by adjunct faculty). 4. 40 students cohort at UChicago's program vs 80+ student cohort at Georgetown. And the academic background of student cohort at UChicago's program will be higher than those at Georgetown. I really appreciate advice and insight into these two programs. Thank you!
  10. I received offers of admission from UChicago Harris (MSCAPP) and CMU Heinz (MSPPM: DA track), and I'm certain that there are others out there facing the same choice. For what it's worth, Heinz has offered more funding than Harris (once again, I doubt that I'm the only one in this situation). I'm not even sure how to weigh the pros and cons of the two programs. To people who are currently in one of the programs, how do you feel about it? And to those trying to decide between the two options (or held offers from both places in previous years), what factors did you consider?
  11. I am admitted to the master of data science program at Harvard and MIIS at CMU. I am trying to decide between the two programs. Harvard's brand name is really attractive, but I don't know if a master is considered an alumnus. And also CMU is number 1 in CS field. I went to Umich for undergraduate and I majored in computer science. My current career goal is to become an SDE or data scientist after graduating from grad school. But I didn't completely rule out the possibility of getting a Ph.D. I would really appreciate any advice!
  12. Just wanna start a post for Columbia Data Science 2019 fall applicants. Has anyone heard back yet? Or what is your process?
  13. I'm interested in applying to Stats and Data Science MS programs. The USNWR and AMSTAT top schools list is helpful (for stats), but I'd like to see a larger list. I've come across some interesting programs just by looking up x school (not on the best ranked lists) and looking up programs they're offering. Does anyone know of any resources that post a list of all data science programs and/or statistics programs in the United States? This resource from CSU East Bay is kinda what I'm looking for, but it's dated. Looking up data science programs is trickier-- no USNWR or AMSTAT lists, but instead a lot of "20 Best Value Schools for Data Science Masters" type results. A little bit off-topic, but should I just stray away from considering schools that don't score highly on USNWR (or are even unranked)? It seems like a ton (most?) of the posters on GradCafe are only seriously considering Ivy-League or similar status schools. I'm sure the elite schools consistently beat out lower ranked schools across most metrics, but is it to the point where I shouldn't even consider the lower ranked?
  14. Hi all, I'm deciding between Columbia's Masters of Science in Business Analytics and University of Michigan's Masters of Science in Data Science program. Since they are in different industries, I'm very conflicted. I got waitlisted from NYU and UW Data Science, got accepted to Cornell's MPS in Applied Statistics (Data Science), ORIE at Cornell Tech, and Georgetown Analytics. Still waiting from Brown, PENN, LSE Data Science. Economics major and Statistics minor at a top 3 liberal arts college, with some cs background. I think my end goal is working as a data scientist at a consulting/finance firm, but I'm open to other data science roles. Not interested in PhD. I was leaning towards Michigan because of technical complexity, so I'll have a wide variety of career options, but everyone's telling me to choose Columbia because of its name value, resources, and geographical advantage (i.e. recruiting and networking). I have a week to decide - any advice/input would be appreciated!!! Thank you!
  15. Hi, I'm an ivy grad who majored in Economics & Statistics, 3.7 cumulative GPA, 167 Quant/165 Verbal on GRE. I've been doing strategy for a big tech company the past 2 years and been functioning as the go-to analytics/data science person on the team. Now I want to make a full-on transition to data science (goal is to become a ds at a startup!) and am realizing that I need more training in math and statistics to thoroughly understand the stuff I'm doing. Data Science Masters at Stanford, Harvard, and Columbia are my top choices. I'm also considering Statistics masters as well, since I want to hone in on the modeling/statistical part of data science. Although I have a ton of projects and experience at my current job & Kaggle applying machine learning/statistics, I don't have any research experience. I took 2-3 machine learning/data mining courses and 4-5 econometrics classes in college, and plan to get 2 rec letters from each field. I also did an online certificate program from MIT in Big Data. Do you think I stand a chance for statistics masters or data science? Would also appreciate any and all tips on crafting out my SOP. I'm so much more used to writing professional resumes... Thank you!
  16. Hi everyone I've worked as an analyst for 3 years and am fascinated by the application of statistics and related sophisticated algorithms by tech firms to drive business value. I want to deepen my knowledge base of the same via higher education. While researching programs, it appears to me that Analytics and Data science programs are sort of general purpose and don't go quite deep into the subject matter. Due to this I've been considering Statistics / Operations Research / Management Sci MS programs. Thoughts?
  17. Hi! I'm a recent graduate planning on applying to PhD programs in statistics or data science for Fall 2020. My research interest lies in the field of Natural Language Processing. Undergraduate Institution: Western-style university in Central Asia (Nazarbayev University) Majors: Mathematics, minor in Economics GPA: 3.57/4.0 (lower in the first year when my major was Chemical Engineering, and higher after I transferred to Math) Type of Student: White Female Relevant Courses: Math & Statistics: Calculus 1, 2, 3 (A, A, A) Linear Algebra (A) Probability (B) Applied Statistical Methods (A) Math Statistics (B) Regression Analysis (A-) Design of Experiments (A-) Intro to Proofs (B+) Real Analysis (B+) Nonlinear Optimization (A) Actuarial Math (A-) Computer Science: Programming for Scientists and Engineers (A) Performance and Data Structures (B+) Statistical Programming (A) Other: Econometrics (A) Economics of Financial Markets (B) Capstone Project in Math (A) GRE General: Q 167 (91%) , V 152 (56%), AW 3.5 (41%) Research Experience: My research was generally focused on the development of computationally efficient and interpretable algorithms for obtaining word embeddings and sentence embeddings. First publication: Springer "Lecture Notes in Computer Science", topic: NLP (word embeddings), first author, conference: CICLing 2019, top 10% of papers Second paper: topic: NLP (sentence embeddings), submitted to AAAI 2020 Research internship in South Korea (UNIST), topic: networks theory In plans: research internship at KAUST 1,5 years experience of working as RA Work Experience: Currently working as a Data Scientist in a Venture company Letters of Recommendation: One from the research advisor (I also took 3 classes from him) One from an academic advisor (He is currently working at the University of Minnesota) One from a professor of Nonlinear Optimization (previously he worked at University of British Columbia) Concerns: This year I was accepted to NYU MS in Data Science and UIUC MS in Statistics, but to the several financial circumstances, I was not able to join any for Fall 2019. That is why I changed my plan, and now I want to apply to the PhD program which could possibly provide the assistantship. I want to continue my research in the field of NLP, but after a search, I realized that most of the professors interested in NLP are working in CS departments (or even in linguistics), but my background is mostly related to Statistics. My dream university is NYU (Courant), but I am not sure about my chances. I will be happy to read your advice and grad schools suggestions. Thank you very much!
  18. Hello, I have got admits in the following universities and programs: TU Kaiserslautern - M.Sc. Computer Science RWTH Aachen - M.Sc. Data Science Paderborn University - M.Sc. Computer Science OVGU Madgeburg - M.Sc. Data & Knowledge Engineering Universitat Bamberg - M.Sc. International Software Systems Science Please suggest the best/suitable program with respect to research prospects, job opportunities, long-term/short-term benefits?
  19. ECE undergrad from a top 20 university in India. 329 GRE, 9.32/10 GPA (ranked third by GPA in my major). Taken most of the basic and some advanced coursework in CS (around 12 courses), with a number of MOOCs to augment it. Two month-long software developer internships at startups, one research internship at my university in ML and Networks, one research internship in Germany working on state-of-the-art Neural Nets for combinatorial optimization. One semester research project submitted as a paper to a top Robotics conference, and one research project coming up with Mercedes Benz India working on autonomous driving. Do I stand a chance in the top 20/top 30 MS CS programs? My list: UIUC, UCLA, UCSD, Georgia Tech, Northeastern, Brown, USC, UMass Amherst/CU Boulder, UToronto
  20. Hi guys! I just got admitted to these school for the data science program. I want to know your thought about these schools in terms of job prospects, education, etc. and let me know what school i should go to pursue my MS. Thank you!
  21. I have an admit from ucsd(no funding) vs kth(tution scholarship). I'm really confused which one to choose. UCSD is more recognized and is near silicon valley, but kth will allow me to be debt free after studies. But wages in sweden are low. Can anyone give their suggestions/share their experiences at any of these?
  22. I (international student) got accepted into these two programs, which are quite different, but I believe both could lead me to a good position as a data scientist, in the US preferably. I am struggling to make a decision. On the one hand, NYU's 2-year Master is a top-10 program in the subject that would allow me to dive deep into data science core subjects as well as to do an internship during the summer. I feel that I would learn a lot in this program, get to know a commnity that is doing cutting edge work on the field and, hopefully, access good job opportunities The program is expensive, though, and I have not received any financial support. On the other hand, Berkeley's 1-year program combines technical courses with business-oriented topics. This means there will be considerably less time to invest in pure data science work. IEOR is a very broad area but ideally I would specialize on analytics, which could get me closer to the kind of jobs I want. I know MEng alumni have pursued careers in data science and similar positions before. Of course, this program has Berkeley's amazing prestige and faculty behind it, plus a lot of networking oppportunities. Besides, it will be significantly less expensive than NYU's MS, since this is a one year program and I have been awarded a $16k grant. Any thoughts on making a decision? Thank you!
  23. I have got admission from BGSU(Ph.D. in Data Science) and CMU (MS in Applied Statistics & Analytics) Which one should I go for? I am referring to learning and future job opportunities. Thanks
  24. Hi everyone, I'm planning on applying to Masters programs at the end of this year specifically ones that intersect in Data Science + Public Policy. I have a BS in Geographic Information Science so my main interest is in spatial analytics and recently its been mainly in urban informatics. My background isn't in computer science, my degree only required minor levels of Python, SQL, & stats so I'm currently taking some comp sci and higher level math courses while I work. I'm looking for any programs that would fulfill these requirements of Data Science + Public Policy (Spatial Analytics/Urban Informatics) I've seen this list https://www.mastersindatascience.org/specialties/best-data-analytics-degrees-for-public-policy/ but I'm searching for more lesser known programs bc my GPA isn't the greatest. I'm actively taking post-bacc courses to remedy this. However I still need safe programs. If you guys know of any please post them below. Some examples: University of Missouri (Mizzou) - Data Science (w geospatial concentration) UMBC - Spatial Analytics Pathway More reputable programs I *might* apply to: Northeastern - Urban Informatics NYU - Applied Urban Science & Informatics (CUSP) University of Chicago - Computational Social Science / Computational Analytics & Public Policy University of Pennsylvania - Urban Spatial Analytics
  25. Almost ready to join UBC MDS program for September 2019. (Waiting for Michigan Ann Arbor!) Anyone else joining UBC? Would love to connect. P.S - International Student
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