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Found 79 results

  1. 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!
  2. 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.
  3. 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!
  4. 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.
  5. 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!
  6. 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?
  7. 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!
  8. Just wanna start a post for Columbia Data Science 2019 fall applicants. Has anyone heard back yet? Or what is your process?
  9. 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?
  10. 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!
  11. 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!
  12. 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?
  13. 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!
  14. 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?
  15. 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
  16. 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!
  17. 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?
  18. 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!
  19. 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
  20. 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
  21. 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
  22. Is anyone else still waiting to hear anything from NYU data science/knows how their process works? I saw someone mention that they did in person interviews last week, does this imply that if we haven't heard anything at this point we should assume rejection?
  23. Decisions for M.Sc. Data Science for Summer 2019 at RWTH Aachen are out. What is the expected total incoming strength? Successful applicants are welcome to contact.
  24. Inspired by @bigdatagirl 's idea. If anyone is applying for graduate programs in the Spring or Fall of 2019, feel free to post your profile and the colleges you are applying to. Just interested in what kind of profiles and applicants are out there. Undergraduate Major: Applied Math Institution: TCNJ GPA: 3.1 GRE: 162 Q / 151 V/ 5.0 A Relevant Courses: Regression, Data Mining, Database management, Intro to Data, Data management (taking now), Probability (taking now), Business Analytics (taking now) Applying to: Drexel, Penn State, Rutgers, NJIT, Northeastern, UMDUC, Villanova
  25. Hi all, Hope everything is well for all of you! Congrats for those who got their invitations and offers! I'm not sure if there's anyone in looking at this post and is at the same stage as me: got nothing but only rejection letters (5/9). I applied for 9 PhD programs and haven't heard from Harvard, Princeton, Stanford and UCB, but I see in the cafe that many people have got their invitations, and the interview dates are reasonably close. (One of the disadvatages I have is that I'm an international student, thus we are considered separately because of funding issue.) As a result, I need to move on and work on my plan B. With all the advice I've got from friends, grad students and professors, I don't feel ready to make a solid plan by myself. Thus, I'm posting this up, and, hopefully, we can all share some ideas on how to make an alternative plan. So here's something about me (I'm not sure how detailed should I go for, please let me know if it's not appropriate): I'm currently a senior, international student at UMass Amherst. I'm finishing a dual degree in biology and mathematics (applied/stats track). I have a 3.977/4.000 GPA, and received 40k+ scholarships over the years. In addition to my academic live, I also have 3 years of experience tutoring and 2 years of volunteering (BBBS kid mentoring program). I've only taken GRE once, and I have Q168, V151 and 3.5 (I'll definitely make this looks better if I apply next cycle or later). I'm in the honors college and doing a thesis. I have been in a plant genetics lab since the second month of freshman year, where I had various experience with wet lab experiments and bioinformatics/systems biology analysis. I am co-authoring a paper that will be submitted in February which is about analyzing and interpreting an RNAseq dataset. I'm working with this PI for the 4th year and he said that wrote me a very promising letter. In addition to working with plants, I also had research experience during summers working with mammalian telomeres and interned at MRL at Boston on immuno-oncology targets. As for the computational aspect, my work on analyzing data in lab required me to use R, python and bash scripting. I also had intermediate/entry/entry levels of experience with SAS/Matlab/Java from project-based math/stats courses. My original plan is to go straightly for umbrella PhD programs, which covered computational biology or systems biology. I want to use my advantage where I can do both biology and mathematics and to work in interdisciplinary fields. My passion originated from doing experiments, so I still want to keep up with my web lab skills (i.e. doing gene editing according to the results from computational analysis) which I think would also be valuable when I look for jobs later. For long term goal, I would like to work in the R&D parts of the pharmaceutical industry. From the conversations I had with my co-workers during my internship, career-wise, it would be very helpful to have a PhD degree. Also, I don't want to limit myself to plant biology, so I need the transaction to focus on other systems. Also I want to keep all the lab work I deal with in vitro. However, since the plan going for PhD directly didn't work out well, I need to start thinking alternatives. I think my CV would look better in a year or two when the paper is published (there's another one data analysis based that I'm working on as the first author). Also, there's a gap in between the data analysis I do in the bio lab and what I learned from my math/stats courses: I didn't have experience developing computational/statistical tools. I think it may be a solid plan to do something to fill in that gap. The first thing I'm thinking of is getting a master in biostats. Although the deadlines for submitting applications have passed for a lot of good schools, I'm exploring options that are still available (i.e. Brown, UMich, UMinnesota, UCD, UPittsburgh, CWRU and UMass). One question I have is how much a biostat master degree would help if I want to go back to applying biomedical/compuational PhD programs? I do believe a master in biostats will open a lot of doors if I want to look for jobs, also if I want to switch to tracks such as data science. From what I have seen, all biostats programs offer the opportunity to do a thesis, however, if I want to apply to PhDs during the second year of my master, I don't think the thesis will be ready for publishing and I'm not sure how much points that will add to my application. So should I go for a thesis if I end up going to a master program? The good thing is that, if I stay in the same school, I can finish the master with only one additional year. That being said, if I apply for PhD programs in the next application cycle, a thesis would definitely not in time. Yet, all the courses I take will be very coding heavy and project-oriented so would expand my skill-sets on the computational aspects dramatically. I'm not sure how many bio/mcb master programs are still available now. If not going for biostat programs, I hope to get into schools that may help with my applications later. So please let me know if there's any program worth going for a try. I know the last option I have is the MCB MS at my school, which there's no doubt that I'll get into. One of the reasons I didn't think much of this option is that I need to take classes during the PhD programs anyway so I'd rather do something that I can learn more with the same amount of time and effort. Another option is looking for jobs and gets experiences while working. As an international undergrad, I think it's hard for me to look for jobs in the US (although I have the 36 months OPT available), especially jobs that I can learn as much as a master program. It's hard to imagine finding a job that will allow me to do things that I don't know before (I'm still thinking about filling the gap in my experience/skills). With everything going on in the U.S., I was advised that it's not such a bad idea to look for PhD programs in Europe, since I'll be international anyway. However I have no idea how this would work, so please let me know how I should start looking and what I should be expecting if going to graduate programs in Europe. One addtional note is about grad school funding. My parents are funding me for undergrad (although I tried very hard to get as many scholarships as possible), and they can and are willing to fund for my tuition for master and PhD. However, I find it very not helpful when programs as me to bring my own funding while applying for PhD programs. I completed my undergrad in the U.S. so I'm not eligible for a lot of funding from my own country, also I don't want to sign contracts that force me to go back to work for a few years right after graduation (I'm not against going back but I want to keep all options available). And, to my knowledge, there's no scholarship that I can apply to before being admitted to a program (NSF grant requires citizenship). That leaves me no option to bring my own funding while applying, which makes me less competitive among international or all applicants. I appologized that this is getting way longer that I planned for. Thank you if you have read this far. I'm just going to summary some major questions that I need help with: 1. What can I do better if I apply to PhD programs in the future? (Umbrella programs aiming for computation-based track). Are there any not famous but good phd programs that I can still apply for? I know WPI is still rolling and have a lab that may fit my interest according to a professor I talked to. 2. Is it worth it going for a master in biostats? Is a thesis helpful if it won't be ready as a submitted paper? How much help would it give to a future PhD application (systems bio/computational bio)? What specific programs that are still available? Would I be competitive for such programs? 3. Are there any worthy bio-based (i.e. mcb) master programs still open? 4. Guidelines for looking for jobs as an international undergrad. Is it possible that I can learn how to do more complicated computational analysis even if I had little experience with it before? (Although I can learn from colleagues, I imagine companies will want me to do things that I'm already good at.) 5. Where can I find possible fundings for grad school as an international student? The search engines don't really help much before one is admitted to a program. 6. Any other advice or question? 7. Thanks for reading all these! All the best luck for all of you!
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