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Found 31 results

  1. 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?
  2. I will apply several graduate schools in US, would it be hard to get admissions from any of schools below? here is my profile Status : International / B.S degree in Industrial engineering in Top 10 univ in my country / Currently working for National Army as an info/signal officer (service in duty) Working/Research exp : worked as a research intern in school laboratory(Quantitative Technology Management) for 8 months (proceeded paper related to the project in the lab but didnt published) CGPA : 3.33 / 4.0 Major GPA : 3.66/4.0 (several schools want major gpa and my major gpa is lot better than horrible cgpa...) TOEFL : 103 GRE : havent taken but expect around V160/Q168/W3.5 Relevant courses : Multivariate Calculus(C+..... I shouldve retaken this) Probability theory(B+) Applied statistics(A) Quantitative analytics(A+) Data mining(A) Operations research(A+) Linear algebra(A+) Discrete Math(B+) .... and other many courses provided in industrial engineering at least better than B+ grade And below is my school list Stanford(data science) , Berkeley(IEOR) , Michigan(Industrial Eng) , Purdue(stat) , UIUC(industrial eng) , USC(data science) , GA tech(analytics) , Northwestern(analytics) UCLA(statistics) , NYU(data science) , CMU(Data science) , Washington at seattle(industrial eng) , Johns hopkins (applied statistics) I do think to get ad from one of them is difficult... should I add some safe school in the list? Im afraid I would get all rejection... I ll be waiting for your comment thank you
  3. Hello everyone, Anyone applying to UC Berkeley MIDS program for next spring? I'm interested in the program, but the GRE requirement and the prohibitive cost makes me think twice about my application.
  4. Hi folks, I've been accepted to the following programs: MS in Data Science from NYU MA in Quantitative Methods in the Social Sciences at Columbia (want to pursue the data science concentration) MS in Computational Analytics and Public Policy at University of Chicago Master of Information Systems Management with a concentration in Business Intelligence and Data Analytics at Carnegie Mellon So exciting to have so many options! I think I've probably narrowed it down to Columbia and NYU, because those programs are most narrowly focused on the data analysis stuff I find most interesting, but feel free to persuade me otherwise! I worked at a marketing consulting firm in the analytics department for two years, and then I worked at GlobalGiving, a nonprofit crowdfunding platform for a year and a half. For undergrad, I studied Economics and Professional Writing at Carnegie Mellon University. I've taken some programming here and there, but doing business intelligence work using SQL and Excel has been by bread and butter, so any of these programs would stretch my technical skills. I'm not completely sure what I want to do when I graduate, but broadly speaking, I want to be a data scientist in the social impact space. I could see myself as a data scientist at a crowdfunding site and/or a number cruncher at an international institution like the UN (Global Pulse) or the World Bank. Which of these programs would get me where I want to go? If you can't compare, what could you say about any of these programs? I'm curious about the reputation and name recognition of each. If you graduated from any of these programs, how did you like your experience? For NYU and Columbia especially, these span multiple departments and are really flexible so I'm curious if it's hard to feel like you're part of a community, because everyone is so dispersed. These are also fairly short - Columbia's QMSS is only 10 classes and NYU's MS in Data Science is only 12 classes. Did you feel like the program stands alone and did you have enough time and classes to learn what you needed? Thanks for your thoughts!
  5. Undergrad Institution: Stony Brook University (Large State School, has a good reputation for my majors) Major(s): Physics, Applied Mathematics and Statistics Minor(s): GPA: 3.35 (AMS GPA is 3.6) bad grades mostly in sophomore year. Type of Student: International, Male, South Asian GRE General Test: Will be taking soon. Anticipating > 95% V scores but around 90% Q score. GRE Subject Test in Mathematics: How important is it that I take this? I don't really have time to study for another test on top of the GRE and my demanding final year schedule. Programs Applying: Masters in Statistics/Masters in Data Science Ideally I want to apply for Phd programs but given my crappy undergrad record, I've decided to apply for masters and see if I can get into the Phd programs later on. Research Experience: Essentially none. Did some linguistics research not related to statistics with a pretty famous guy but that was a while ago and no paper came out of it. Awards/Honors/Recognitions: Deans List, Physics Honor Society. Pertinent Activities or Jobs: Irrelevant on-campus job for 3 years and currently doing a data analyst internship at a very small marketing agency. Letters of Recommendation: The School is HUGE and all my classes are >100. Its very hard to get to know professors and this is likely the weakest aspect of my application. I will get recommendations from professors I've taken courses with and gotten As but that's about it. I don't even expect them to remember me or know who I am and I just don't see any way around this. I can try to cultivate some relationships till application time in December but I don't really know how to or how successful I will be. Courser Work: Math and Stat Courses: Survey of Probability and Stats (A), Probability Theory (A-), Combinatorics (A-), Data Analysis (A), Deterministic Models (A), Statistical Lab (Basically a course on R programming and SAS), Calculus 1,2,3,4(Taken in Sophomore year so grades are mostly Bs and a C in multivariate), Linear Algebra(A-). Probability and Statistics for Data Science (In Progress) Physics Courses that may be relevant: Quantum Mechanics (Some probability and lots of Linear Algebra)(B-), Statistical Mechanics (Lots of probability)(B-) Computer Science courses: Object Oriented Programming (A), Data Structures (A-), Analysis of Algorithms (In Progress), Probability and Statistics for Data Science (In Progress), Computational Geometry (combined course by Computer Science and Applied Math department also in progress). Online MOOCs: 4 course specialization in Python by Uni on Michigan (Coursera), 10 course Specialization on Data Science by JHU (Coursera), Machine Learning Course by Andrew Ng (Coursera). Applying to Where: Iowa State - MS Statistics UW Madison - MS Data Science UC Davis - MS Statistics U Iowa - MS Statistics Rice - MS Statistics Rutgers - MS Data Science (Statistics track) UI Chicago - MS Statistics U of Colarado Denver - MS Statistics USC - MS Data Science UIUC - MS Statistics UT Austin - MS Statistics Georgia Tech - MS Statistics Northwestern - MS Analytics JHU - MS Statistics Some of these schools are obviously reach school and are not realistic but I'm extremely worried about my GPA and recommendation letters. If this doesn't work out for me, I essentially have nothing to turn to so there's a lot riding on this. My GPA is mostly bad cause of sophomore year courses which included important things like multivariate calculus and Physics courses which are either freaking hard at this school or just didn't jive with me. Math and Stats otherwise is pretty decent. How can I improve my application? Is there anything here I can leverage? How can I build enough rapport with a prof to get a good recommendation letter in 1 semester? Do you have any other advice or suggestions? Any other programs you think I should consider? Any other Specific courses I should take?
  6. NYU MS Data Science F17

    So it's already late March and browsing through the results it doesn't look like anyone's gotten a notification of acceptance or rejection? Has anyone heard an update yet?
  7. Anyone Can Be a Data Scientist

    I know I know, the title sounds extremely far fetched. Not anyone can be a data scientist... right? If there is anyone that can definitely be a data scientist, it's us statisticians. I haven't seen a field where our knowledge is evermore utilized, to the point where a true shift in demand is asking each & everyday. Oh sure, we always say 'but there's so much coding involved' or 'I rather do modeling than clean data.' Wow, newsflash: kids in the third grade are learning how to code: you should too; & think about it: if all data was clean, would we have developed so many algorithms to accommodate the data without destroying information? Dirty data leads you to more modeling discoveries!!!
  8. After much consideration, I have narrowed it down to these 2 programs. I came from a Biology and Statistics background in undergrad. However, I mostly had experience on wet lab biology as I thought I wanted to go into research, which I didn’t. Long story short, I want to pursue data science as my career now, and I’m wondering which program would be more suitable for me. I’m more inclined towards Galvanize as it’s more industry-focused and the internship will give me so much more hands-on experience. I also think that SF is also more beneficial in terms of networking with people in this field. Nevertheless, 2 years at UMN would give me a more solid background, and cost of living in Minneapolis would also be cheaper. With my goal of getting into the industry right after completing the program, which one do you think would be better? Thank you.
  9. No, not quite as important as Lebron's decision, but I do have to make one in the next 10 days or so. I have 2 offers for Masters in Data Science programs from the following universities: University of Washington at Seattle - Masters in Data Science Tuition: ~45k, 5k department scholarship for 2017-2018 Pros: Has better regarded comp sci and applied math program, smaller cohort (~50), cheaper, Seattle is a big tech area with lower cost of living, Cons: Relatively new program, no graduates yet to give employment statistics, Seattle is gloomy NYU - Masters in Data Science Tuition: ~62k, no funding yet Pros: More established and high profile program, NYU really looks out to make sure their students get jobs/internships, more DS faculty members to work with Cons: more expensive both in tuition and cost of living, have to move to NYC (far from california), larger cohort expected (up to ~100) I currently live in silicon valley, and plan to work probably in tech after graduation, although I am open minded. I want to conduct some meaningful research while I am at either school, and have contacted several professors. I can probably round up another 5k or so in external scholarship/grants before fall, but most of the cost I will have to foot via my saved $ unless I do RA/TA-ships. In fact I suspect my decision will come down to what individual professors can offer me in terms of research work/funding from either school. Thoughts?
  10. I've already considered about my decision for two days but I cannot figure out anything. I'm graduating with a statistics BS this spring, and I plan to become a data scientist after earning my master degree. NYU definitely has a better location, and the program is very good and popular. I believe it's easier for me to get a job if I choose nyu. However, Duke is a world-renowned school and the MSS program is also among the best nationally and internationally. I just don't which one to choose, and I have a strong feeling that the decision will affect my future...
  11. Hi all, I'm an international relations major who speaks a few lesser-known languages with several years in management consulting under my belt, and I'm planning to apply to urban planning/public policy programs this fall. I'd like my classes to have a strong international focus as well as give me a solid understanding of quantitative (statistics) skills and technical (GIS, data management, data visualization using R, Python, etc) skills, as I didn't get these in undergrad either because they didn't mesh with my qualitative studies or were too stovepiped at the time in the engineering/math departments to be widely applied to political science/international development. I've considered a public policy master's, but urban planning seemed like a great fit for my creative interests in design and interests in working on international issues where my language and cultural knowledge could be put to use. Sound logical, or too romanticized for someone with no experience in the urban planning field beyond some GIS work? Beyond grad school, I'd like to be competitive at either an international development group in the private sector (tech startup?), international finance (World Bank), or NGO sector. Here's my list of schools: MIT DUSP Harvard HKS/GSD Columbia GSAPP/SIPA (Urban Studies concentration) UPenn MUSA And a few others with less of an explicit Urban Planning emphasis: Tufts Fletcher UChicago Harris/Computational Analysis A few questions on both grad schools and careers: 1) Any schools I'm missing that I should check out? I've heard the Ivies may not be as important with their brand-name as say for business schools, but the programs look interesting. I'd like to be in a major city for networking purposes as well as to get some exposure to local infrastructure/planning programs, even though I don't see myself working in local or state government long-term. This list was also put together to give me the most flexibility in terms of career options in the field. 2) What are some urban planning jobs outside of local or state government that do work or plan internationally? I'm aware of a few civil engineering or international development groups like AECOM or Louis Berger, but welcome any other suggestions. Thanks for any advice you can provide!
  12. Hey, Profile - BTech+Mtech IIT Delhi, Electrical Engg, GPA = 8.5. So far have worked with big brands as a senior business analyst (~2.5 years). Toefl - 107 ( 28, 29, 30 , 20 in listening ) GRE - 323 ( Q - 166, V - 157, 3.5 Awa) Have got an admit in MS Data science from Columbia. But I have not really done data science in the last 2.5 years. I can babble a few things related to machine learning. I see that most of the people who go to Columbia have a few years of experience as data scientists (DS) or at least a few meaty projects in DS. So,I am scared of taking the chance and accepting the admit. It is big money. Should I apply again next year? (Columbia doesn't defer admits).
  13. I appreciate any feedback! I know my profile is very very VERY weak, I was not aware that I wanted to apply for PhD programs until a few months ago, and I wasn't trying my hardest Freshman, Sophomore year. However, I just want to know if I have a chance getting into ANY PhD program for Statistics or Data Science. I'd prefer schools in the NJ, PA, NY, MD, DE area! Please be honest with me, if I have no chance getting into any PhD programs in any school, I need to know! Undergrad Institution: The College of New Jersey Major: Mathematics with a specialization in Statistics GPA: 2.8 (this will definitely be above a 3.0 by the time I graduate) Type of Student: White Female Upper Division Courses: Math: Calc III (C), Linear Algebra (C), Probability (C, I'm retaking this class right now and will get an 'A'), Mathematical Statistics/Statistics Theory (retaking this class next semester, will be 'A'), Bayesian and Computational Statistics (B-), Regression Analysis (B+), Multivariate Analysis (B), Design of Experiments (B-) Next Semester, and Fall 2018: Operations Research, Probability (retaking), Mathematical Statistics (retaking), Real Analysis, Statistics Capstone Others: Data Management & Analysis (A), Gen Chem (B), Physics (B-), all of the rest are liberal learning classes and I got A's or B's in all of them. GRE: haven't taken yet. Awards/Honors/Recognitions: - Pertinent Activities or Jobs: Interning with a government agency, helping them with a project that involved statistical analysis and coding in SAS and R, will be the co-author of a published report. Letters of Recommendation: -Two statistics professors (that I've had many classes with) - My data management and analysis professor Plan to apply to (Phd Statistics Programs): Anywhere where I can have some sort of a chance getting in. I need help with researching schools. Is there a good website where I can see the percentage of applicants accepted, average GRE score, etc. Thank you so much again!!
  14. GRE: 321 TOEFL: 101 Work experience: 2.5 yrs as a data analyst CGPA: 7.7 (IIT Kharagpur 2014 dual degree graduate) Looking for Data Analytics and similar programs Shortlisted: NCSU UIUC U of Cincinnati U of San Diego Georgia Tech But I feel like they all are too ambitious for my profile. Please let me know your advice and suggestions. Much appreciated. Cheers
  15. Hi! Degree: Econ bachelor from top15 Chinese Univ. with the best econ school in China; UPenn MS in policy&data (could have finished in 2018 but I am applying for the next fall so no master degree when got admitted) GPA: 3.48(general), 3.64(major), 3.75(last two years); no GPA yet for the master at Penn GRE: 167q+154v+3 Course: Undergrad-Calculus, Linear Algebra, Probabilities&Stats, Database, Applied Statistics; Grad-Programming Languages and Techniques, Applied regression, will finish modern regressing and forecasting methods next semester; MOOCs-1 for data scientist toolbox, 1 for R programming, 1 for Python data mining Skills: Familiar with Python, R, Java, Stata, Processing, MySQL Research: 1 national level research using econometric model, processing house-hold survey data in Stata; 1 job-oriented project using R, similar to typical work of a data scientist Interns: one business analyst, one information assistant, one public administration, all in small firms/organizations No strong Rec Letter. Apply for: MS in data-related programs and transfer-friendly cs/mis programs MCSE: Rice-MCSE, Harvard-CSE, Data Analytics: UCB-EECS(data science and system), Cornell-MPS, Columbia-Applied Analytics, CMU-MITS CS/MIS: UChicago-CS, CMU-MISM, CMU-Ebiz, UPenn-MCIT Am I aiming too high? Anyone I could delete from the list? Any info and comments are welcome!! Thank you so much! I feel so frustrated in the transfer period.
  16. Profile Evaluation

    Hi Guys, Could you guys help me shortlist 3-4 universities for data science?Please evaluate my profile:10th : 92%12th : 89%UG Course : BE (Hons.) Electronics and Instrumentation + MSc. (Hons.) EconomicsUG CGPA : 6.23 (Low!!! :()College : BITS Pilani University MOOCs : 1, Data science related from coursera (Planning to complete one more by Dec)GRE : 170 q +153vInternship (1 year) : National Council of Applied Economics Research2 Projects (working with mentors). These reports were published:1) E-Readiness Index of 2012 (Department of Technology, Government of India)2) Aviation Meteorological Services, Sea,Water Desalination, Ornamental Fish Culture, and Lobster and Crab Fattening:Economic Benefits, Project Impact Analyses and Technology Policy (link: ex :1) 18 months as a business analyst in a pure play analytics firm2) 19 months as a data scientist for a top retail analytics firm operating across 13 countriesSkillset: Extensively used R, Python, SAS, SQL, Tableau in projectsProjects on the ML front: Supervised learning : xgboost, linear, logistic regressionUnsupervised : Clustering, collaborative filtering LORS: 1 from work manager, 1 from data science director, 1 from ex-assistant-prof of University or oregon (now Fellow, NCAER)Universities that I am looking for:1) CMU : MSCDS 2) University of Virginia : MSDS 3) Indiana Uni (Bloomington) :MSDS 4) Uni Cincinatti : MSBA with data science certification1) 5) University of Rochester : MSDS (If the programme is good, currently no reviews)6) Northwestern University :MS in Analytics 7) University of San Francisco : MS in Analytics8) University of Minnesota :MSDS 9) NYU : MSDS What are my chances in these universities? What other universities can I look for Data Science?What other universities should I target?Should I do some online courses to offset by college cgpa?Thanks!!
  17. Hi, I'm a Mechie by qualification, BA by profession looking for a ML transition. Owing to my diverse background I've realized that if I want to get close to the ML space, rooting for MS in data science is my best bet. Profile - Mech Engg; CGPA: 7.44/10 (~3.2/4) GRE: 323 (159V; 164Q; 3.5AWA) 3 years of relevant work ex in Data analytics ML research project at a leading Space Tech firm Reccos: 2 from the work and project ex (good); 1 from coll dept prof (moderate) Need help in bucketing the following universities for MS in Data Science into Safe/Moderate/Ambitious - NYU Columbia UWashington U British Columbia NW MS in Analytics Thanks! and any other university/course suggestions would be appreciated! (if I have better chances in any of those - great!)
  18. MS in Data Science/Profile Eval

    Hi, I am interested in a Graduate Program in Data Science in the US. I have a GRE score of 319 (V:158, Q:161, AWA: 4.0). I have been working in Business Intelligence domain for about 6 years now as a developer. I have a Bachelors Degree in Computer Science with a CGPA of 7.95/10 and a strong extra curricular activity background at University level (backed by certificates). I am very interested in the MSIM program of CMU and MS in Statistics of Stanford University. I am planning to apply to these programs(along with other programs of course). Can someone please take a quick look at my profile and let me know if I stand a chance of getting into these two universities? Am I being too ambitious with this score? Thank you. Cheers, Krishna
  19. Hi, Below are my GRE scores : VA : 161 QA : 170 Total : 331 AWA : 3.5 I'm planning on applying to the data science or business analytics courses in the top US colleges. Please let me know, what my chances are (I have good acads, extra curricular and 3 years work ex).
  20. Should I retake the GRE

    I'm an international student from China who recently graduated from UCLA with a 3.5 overall GPA, and a 3.8 statistics major GPA, and am going to start my statistics master's program at Columbia University this Fall. I plan on applying to a PhD's program in statistics after I graduate from Columbia but I don't know if I should retake my GRE I have a 170 (98%) on Math, 163 (92%) on Reading, and a 4 (56%) on writing. I am preparing for my GRE Math subject test but I don't know if I should retake my general GRE because I only got a 4 on writing. My dream schools are: Stanford Berkeley Chicago Harvard Washington Columbia University Since those are all competitive universities to get into for a PhD in statistics, I'm conflicted because I don't know how much getting a 4 on my writing matters? I really appreciate every advice. Thank you all in advance.
  21. Hey, I was wondering if anyone knows of any good grad programs that focus within both IR and data science or applied analytical research? It seems like a lot IR or IA programs do have a applied analytical approach to their curriculum, but I am not sure if they are specifically the same as or similar to the actual data science program in terms of the quantitative aspects in relations to computer programming languages like R, SAS, SPSS, or MySQL. I know that the programs I am looking for do include a bit of quantitative methods in research and some R programming, but I am not sure how in depth they seem to be. I want to find a program that will be within International Affairs, but on the quant and tech side in terms of being an analyst. I know I could get a MS or MA in International Relations with a professional certificate in data science that are also offered at the schools I am looking into. Its just hard to find any other dual master programs for what I am looking for. It seems I have to get two separate degrees within both field. Overall, my perspective career goals are to work within IR and to also have the skills and educational background in data science/IT, and applied quantitative research methods so it can look more into applied quantitative IR research, or consulting. I have a BA in Political Science and I have a little bit of survey research, data collection, and R programming and Excel skills from when I was in undergrad via work and classes. I am also taking the Johns Hopkins Data Science Specialization certificate program online to get more of a feel of data science and learn the fundamentals of programming languages more, generally speaking before I decide to jump into any grad program. The only programs I know that are like this are the Columbia dual degree program QMSS and MIA programs
  22. Hi, I got admit from NCSU and USC for MS in Data Science for Fall 2016. Could you please suggest between the two? P.S : I know USC is a better college in terms of general ranking. But i want to know particularly for Data Science specialization, which would be a better option?
  23. Hi Guys, It’s so inspiring to hear everyone’s stories. Good luck to everyone! I wanted to introduce myself to see if anyone is making a similar journey, or has any opinions. I’m a 25 year old medical doctor from Australia, and just finished my internship 4 months ago. I’m planning to apply to Masters of Science / professional masters programs this year for 2017 mid-year entry. I’m considering bioinformatics / computational biology, or computational neuroscience, or some field in computer science. Since high school, I’ve done a Bachelor of Science degree (3 years, accelerated into 2) majoring in Biomedical Science, and a post-grad Medical Degree (MBBS) (4 years), both from a University in the top 50-100 globally. I’ve finished my internship and received general registration in Australia. The Dream: I’ve decided I want to become a data scientist and work somewhere in biotech / med-tech / genomics / machine learning. I’m inspired by Google's DeepMind, and their work with Atari games and AlphaGo - designing incredibly sophisticated AI algorithms. I think this heralds an era of disruption by AI of many professional industries that depend on thinking skills. I’m also inspired by Craig Venter’s work creating synthetic genomes for viruses and bacteria (the ‘first synthetic life’) and I’m excited about the promise of using synthetic bacteria to process pollution, create cleaner fuels and sequester carbon. I think the two fields - artificial intelligence and synthetic life, will redefine the human condition within our lifetimes. And I think the key nexus of them is data science. I would love to build a career in this area, and work in tech startups in the bay area in San Francisco. The Reality: I currently have no research experience, minimal stats / data science and minimal computer science understanding (and no tertiary study in the area). My Plan: This year I’m working as a doctor about 30 hours per week and: 1) doing a bunch of courses in coding, machine learning, and data science 2) saving money to pay for the masters 3) get some experience in research in biomedical science I’d love to hear any thoughts on the following: Is a Computer Science MS realistic? I’m more interested in AI than biotech. Would I be a realistic candidate for top CS schools, with no tertiary experience in CS? I had strong marks in high school advanced maths and physics, but I’ve spent 7 years studying and working in biology and med. I can do 10-20 hours per week to up-skill in this area (roughly 6-7 months before applications are due and 16 months before the 2017 class would start) How much scope is there for CS electives in bioinformatics? I figured bioinformatics may be a realistic way to sneak into CS courses (like AI and robotics). Converting GPA: My GPA in science is 6.0 and my medical degree, 5.46 (both out of 7). 6 is a distinction average, and 5 is a credit average. I haven’t been able to work out how my GPA converts to the US though. What schools should I aim for in CS and bioinformatics? My list after limited research looks like this: Stanford UC Berkeley MIT Carnegie Melon Caltech Johns Hopkins Cold Spring Harbour Harvard Georgia Tech Oxford Cambridge Princeton Imperial College London UCLA UCSD Then a bunch of others in the top 50-100 Again, best of luck to everyone! If you’d like to discuss anything further, please reply here or PM me!
  24. Got accepted to both programs. Goal is to be working in places like UN Global pulse which use tech methods to solve public policy problems. With this I know that Harris' MSCAPP program will fit my description to a T. And I also like the programming courses they have, which keep my options open if I even want to move to the tech/private sector. However, the NYU have advantage in location. I'm also an International Student so some focus on International Policy would also be more applicable to me in the long run. Any thoughts?
  25. Hello, I am one of those who are joining the hype of data science and statistics. This year, I applied to several statistics, data science programs, and today, I received all notifications from the schools that I applied to. Here is the list of schools that I applied and the status of each application Duke Statistical Science Masters - accepted Carnegie Mellon Masters in Statistical Practice - accepted Columbia Masters in Data Science - accepted New York Masters in Data Science - rejected Columbia Quantitative Masters in Social Science - accepted New York Masters in Applied Social Science Research - accepted Penn State Masters in Applied Statistics - accepted So, I am having a big problem in making a decision on which school to attend this fall. Part of me says that I want to join the data science hype and attend columbia, but unlike NYU program (which I got rejected), Columbia seems to be less flexible with its curriculum and with limited scope of learning material. Besides the machine learning course, I cannot find much difference between Columbia's data science program and Carnegie's master's in statistical practice program. Duke has fantastic statistics program, but I am not a big fan of suburb locality. What are the merits to attending data science program compared to attending traditional statistics program? Will people with data science degree have significantly better employment options than people with statistics degree? QMSS also seems to be a neat program. I want to receive some feedback from fellow data scientists and statisticians!