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edwardsaid

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Everything posted by edwardsaid

  1. If you're looking for flexibility and a shorter program, QMSS is great. If you're looking for a longer program with more teaching, go for MACSS. Otherwise, both programs are very similar. QMSS is particularly great for those with strong goals in mind.
  2. I'm a QMSS student and I can attest that the program is great if you intend to go into public policy. There's a lot of alumni placed in prestigious think tanks like Brookings. The flexibility of QMSS is a pro-you can take classes in the Econ department, in SIPA, in business, etc. You can definitely tailor your classes to your goals. And QMSS teaches you coding in both R and Python (and even SQL, AWS and other big data tools). Another program is the NYU A3SR. It's headed by Jennifer Hill who is a close colleague of Andrew Gelman, the founder of our program.
  3. I took a PoliSci grad class at Columbia and it was applied regression. It was def not for the faint of heart; I was lucky I knew R because the class moved really fast and the beginners were falling behind. From what I've heard, the workload is manageable but it requires you to prioritize certain classes and be highly organized. 20-40 page paper assignments are very common and you're expected to have some (at least major works) familiarity with the literature. Also, Columbia's PoliSci is HIGHLY quantitative-be ready for this aspect. Take an intro to R class, review your basic stats (up to linear regression), read up on linear algebra, multivariable calculus and real analysis (if possible).
  4. Former think tank intern here. I was an intern at AEI and they hire based on academic achievements and research needs. My position required strong Arabic skills, which was a rarity. Other than that, it's very much based on luck because I applied very early.
  5. PROFILE Type of Undergrad Institution: Top 10 LAC (NESCAC) Major(s)/Minor(s): International and Global Studies/Middle East studies Undergrad GPA: 3.85 Type of Grad: Well-known Quantitative Social Science prog in Ivy League Grad GPA: 4.00 GRE: V:166, Q:164, W:5.5 Any Special Courses: Machine Learning, Quant Soc. Sci. Methods, Intro to Computing, Econ Stats, Linear Alg, Calc I-III, Adv. Arabic Letters of Recommendation (future): undergrad academic advisor (untenured asst. prof in CP), RA supervisor (untenured asst. prof in CP; in my research area), and either dept chair (Quant Social Science) or undergrad thesis advisor (religion) Other: RA to NLP polisci research project, internships in prestigious DC think tanks Areas: CP, Methods. Topic: political violence, social media, Middle East, Arabic NLP I'm eyeing top PoliSci PhD programs in CP, esp. those with research projects in social media and politics: Princeton, Stanford, UChicago, NYU, UMich, MIT. I realize that my GRE Q score is on the lower side but my grades in quant classes can make up for that (?). I'm also already doing research in my field with a Princeton-based team so hopefully that'd improve my chances for Princeton. Please let me know your suggestions/comments/advice!
  6. Hi, I'm currently facing a dilemma. I just got admitted into two prestigious master's programs in quantitative social science: Columbia MA in Quantitative Methods in the Social Sciences and LSE MSc in Applied Social Data Science. I'm a 2019 graduate from a top 10 liberal arts college who majored in International Studies and I intend to transition into a career as a data scientist or a data analyst, preferably in healthcare tech or in fintech (I'm currently an intern at a prominent national security think tank in DC and I just realized it's not for me). I applied to these programs also because they provide good preparation for a PhD in political science, which I'm interested in pursuing later. My question is considering my background and interests, what do you think is the more appropriate program for me? I list some pros and cons for each program: Columbia QMSS Pros: Great variety of classes. Very flexible and interdisciplinary. Allows me to specialize in data science while still taking a polisci methods class. Small program size with dedicated faculty Research assistantship opportunities Access to Data Science Institute and career fairs Great track record of sending graduates to top PhD programs Cons: Expensive (~$80k tuition) Cost of living in NYC LSE Applied Social Data Science Pros: Solid curriculum. More tailored towards a career in data science Half the price of QMSS Small program with a dedicated research cluster within LSE Access to LSE's international network (esp with Europe and proximity to finance in London) Cons: Very young program. Doesn't have an established alumni network in industry and academia. Research project component does not match rigor of QMSS's thesis component, hence may not be as good of a prep for PhD Unclear of how the degree would be received by potential employers
  7. It's the MSc in Applied Social Data Science. I applied to both but it seems like QMSS has more course options and it's more flexible. LSE's program is significantly cheaper, though.
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