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Fall 2021 Data Science/Analytics Applicants


KMickey

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32 minutes ago, lavafish said:

@diplodocus_ I have some similar admits! Also got into Stanford/MIT/Columbia, and rejected from Harvard (lol).

 

My impression is that Stanford's program is the most selective and probably the best for Silicon Valley tech. Personally, I'm also heavily considering MIT's MBAn because I prefer the east coast. I think the MBAn has a couple of other nice features that stand out, such as the 1) tight-knit cohort/sense of community and 2) great professional support. MIT's program also seems more applied than Stanford's program, if you have any preference on how theoretical v. applied the curriculum is. Another difference between these two schools that stands out is the length-- I do like that Stanford's program is a couple quarters longer and accommodates a summer internship.

Columbia is a great school for undergrad, but I have the impression that its Master's programs have very large cohorts, so there doesn't seem to be the same sense of community at the grad level. I also heard from a Columbia alum that the DSI classes are mostly night classes to help accommodate part-time students, if that affects your decision at all. On the other hand, if you want to be in NYC and develop a network there, Columbia should be fantastic for that.

Curious to hear your thoughts on Stanford/MIT/Columbia as well!

Congrats @lavafish! I totally agree with you, after more thought my decision goes down to Stanford/MIT. Columbia initially appeals to me due to the opportunity to network in NYC and the program length, but I also have the impression that they have a large cohort and I would very much prefer a smaller, tight-knit cohort. Their curriculum (in terms of length and mix of classes) is comparable to Stanford, so I'd choose Stanford over Columbia. 

MIT Sloan's resource for professional development seems outstanding to me (they have perfect placement rate). Another great plus in addition to the two you highlighted is the opportunity to conduct research assistantship with MIT professors. It seems like the MBAn program has great career pipeline if you want to do data science in consulting/finance (in addition to other industries - these two stood out to me, just like how Stanford's connection to Silicon Valley tech stood out to me). 

I do prefer Stanford's curriculum in that students get to take more (in terms of units, but also variety) classes focusing on various topics in ML and computing. It is pretty crazy that you can take classes with, and possibly do research with, some of the most influential names in ML (e.g. Andrew Ng and Rob Tibshirani). Another big plus is the opportunity for full-time 3 month summer internship AND capstone project (if you choose to do one for the Practical Component). Also I think last year Stanford admitted ~20 students and MIT MBAn admitted ~50-60 students. 

Personally, I'd like to stay in California, hence Stanford ranks higher. 

These two/three programs are really, really good options to have and I hope we choose wisely : ) let me know what you decide on!

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On 3/20/2021 at 6:32 PM, Sea Salt said:

@two_dicey Congratulations on your decision! NYU's MSDS seems like a fantastic program. What ultimately set it apart from Georgia Tech's MSA?

Really the duration of the program! NYU's program is 2-years which fit my needs better. My undergrad wasn't in STEM and I wanted the opportunity to really immerse myself in the curriculum and feel like I earned the title of "data scientist". NYU's program from what I hear is based heavily on math theory, which is a big plus. Georgia tech is a great engineering school, but the program was only 1 year. Also, my girlfriend's best friends all live in NYC, which made the decision a bit easier too haha.

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Would really appreciate to get an idea about NYU'S MS in Scientific Computing program at Courant. I got an admit there, which is pretty exciting!, and I am curious to know about future job prospects in Computational Sciences, as well as if I could transition into a Data Science PhD or be competitive for a job as a Data Scientist or a Machine Learning Engineer/Scientist role. Please do chime in and share your knowledge about it.

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@two_dicey The added length, inclusive of a summer break to complete an internship, is nice. However, the curriculum is only one semester longer (3 vs. 4). I also prefer a more significant duration, but I'm not sure that's the deciding factor for me.

Accepted:

  • USC MSCS (Scientists & Engineers) - $10k scholarship
  • UPenn MSE DS
  • NYU MSDS
  • GaTech MSA - TA offer (~$17k)
  • Michigan MSDS

I'm having a difficult time deciding between these. Did anyone else consider Penn or Michigan? If so, I'd love to hear your thoughts! Michigan ranks highly in computer science, statistics, math, and engineering, but its MSDS program seems relatively less well known. Any advice would be appreciated.

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On 3/23/2021 at 4:39 PM, Sea Salt said:

 

@two_dicey The added length, inclusive of a summer break to complete an internship, is nice. However, the curriculum is only one semester longer (3 vs. 4). I also prefer a more significant duration, but I'm not sure that's the deciding factor for me.

Accepted:

  • USC MSCS (Scientists & Engineers) - $10k scholarship
  • UPenn MSE DS
  • NYU MSDS
  • GaTech MSA - TA offer (~$17k)
  • Michigan MSDS

I'm having a difficult time deciding between these. Did anyone else consider Penn or Michigan? If so, I'd love to hear your thoughts! Michigan ranks highly in computer science, statistics, math, and engineering, but its MSDS program seems relatively less well known. Any advice would be appreciated.

IIRC there were some applicants who talked about UPenn in the 2020-2021 thread 

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Hey guys, my chances aren't looking that great tbh lol. I want a more applied/professional/career focused curriculum and so I'm trying to decide between the following:

Accepted:

  • USC Marshall Business Analytics

Rejected:

  • UPenn MSE Data Science
  • Harvard MS Data Science
  • MIT Sloan MBAn (Was really hoping to get into this one but didn't even get an interview so hey, I'm just not good enough. It is what it is)
  • Stanford ICME MS Data Science Track

Waiting/Applied:

  • UChicago MS Analytics
  • Columbia MS Data Science
  • UCLA MS Business Analytics

I honestly think my chances are looking bleak and USC was never a school I really wanted to go to but needed an insurance anyway. But based on what I want (mentioned above) and assuming I'm accepted to all the remaining 'waiting/applied' schools, which option should I go for? From what I've read I think UCLA might be the best choice (because they make you do an internship + capstone project and have very good network connections) but UCLA's acceptance rate was something like 6.6% for Fall 2020 (Might get rejected from this too :( ) and UChicago's web page really lacks an substantial professional/career information so idk about them. I've also read/heard things about Columbia's programme that its not as a tight knight community as other schools like MIT MBAn. Any advice for which is best for my professional/career development?

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12 minutes ago, Sea Salt said:

Yes, I think @carolbells picked UPenn over NYU and Columbia. It's probably worth reading through again, though, so I'll check it out. Any info helps. Thanks!

Yes I'm currently attending UPenn and I'm really enjoying it so far. I mainly chose UPenn over NYU because I wasn't a fan of night classes and like the flexibility of UPenn's program. I'm able to take classes in Wharton and count them towards my degree, for instance.

Despite UPenn being a newer program than NYU I found that all of my peers were able to get internships in data science, data engineering, ML engineering related roles for this summer, so employers definitely do not look down on it.

I didn't get accepted to Columbia's program but I would have chosen UPenn's program even if I had gotten in since Columbia's cohort size is quite big, only lasts 1.5 years, and most of their classes are at night.

Edited by carolbells
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3 hours ago, Ramen_Shop said:

Hey guys, my chances aren't looking that great tbh lol. I want a more applied/professional/career focused curriculum and so I'm trying to decide between the following:

Accepted:

  • USC Marshall Business Analytics

Rejected:

  • UPenn MSE Data Science
  • Harvard MS Data Science
  • MIT Sloan MBAn (Was really hoping to get into this one but didn't even get an interview so hey, I'm just not good enough. It is what it is)
  • Stanford ICME MS Data Science Track

Waiting/Applied:

  • UChicago MS Analytics
  • Columbia MS Data Science
  • UCLA MS Business Analytics

I honestly think my chances are looking bleak and USC was never a school I really wanted to go to but needed an insurance anyway. But based on what I want (mentioned above) and assuming I'm accepted to all the remaining 'waiting/applied' schools, which option should I go for? From what I've read I think UCLA might be the best choice (because they make you do an internship + capstone project and have very good network connections) but UCLA's acceptance rate was something like 6.6% for Fall 2020 (Might get rejected from this too :( ) and UChicago's web page really lacks an substantial professional/career information so idk about them. I've also read/heard things about Columbia's programme that its not as a tight knight community as other schools like MIT MBAn. Any advice for which is best for my professional/career development?

I would probably pick Columbia out of those four (I don't know anything about UCLA's program). However, I prefer an MSDS over an MSBA. Although I'm not all that familiar with it, I think USC's MSBA program is solid. Marshall is a top 20 business school, and the cohort is around 150 students with a ~17% acceptance rate. Also, the USC campus is beautiful.

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13 hours ago, Ramen_Shop said:

Hey guys, my chances aren't looking that great tbh lol. I want a more applied/professional/career focused curriculum and so I'm trying to decide between the following:

Accepted:

  • USC Marshall Business Analytics

Rejected:

  • UPenn MSE Data Science
  • Harvard MS Data Science
  • MIT Sloan MBAn (Was really hoping to get into this one but didn't even get an interview so hey, I'm just not good enough. It is what it is)
  • Stanford ICME MS Data Science Track

Waiting/Applied:

  • UChicago MS Analytics
  • Columbia MS Data Science
  • UCLA MS Business Analytics

I honestly think my chances are looking bleak and USC was never a school I really wanted to go to but needed an insurance anyway. But based on what I want (mentioned above) and assuming I'm accepted to all the remaining 'waiting/applied' schools, which option should I go for? From what I've read I think UCLA might be the best choice (because they make you do an internship + capstone project and have very good network connections) but UCLA's acceptance rate was something like 6.6% for Fall 2020 (Might get rejected from this too :( ) and UChicago's web page really lacks an substantial professional/career information so idk about them. I've also read/heard things about Columbia's programme that its not as a tight knight community as other schools like MIT MBAn. Any advice for which is best for my professional/career development?

Hmmm... You didn't apply to NYU's MS in Data Science and Northwestern's MS in Analytics? I believe those two are in the same league as Columbia's MS in Data Science. But since you have only applied to Columbia, I would advice you to pack your bags and head to NYC if you get accepted. All the best!

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On 3/25/2021 at 4:34 PM, carolbells said:

Yes I'm currently attending UPenn and I'm really enjoying it so far. I mainly chose UPenn over NYU because I wasn't a fan of night classes and like the flexibility of UPenn's program. I'm able to take classes in Wharton and count them towards my degree, for instance.

Despite UPenn being a newer program than NYU I found that all of my peers were able to get internships in data science, data engineering, ML engineering related roles for this summer, so employers definitely do not look down on it.

I didn't get accepted to Columbia's program but I would have chosen UPenn's program even if I had gotten in since Columbia's cohort size is quite big, only lasts 1.5 years, and most of their classes are at night.

Hey, @carolbells, thanks for the update! I’m glad that you’re enjoying Penn.

I have some questions if you don’t mind.

  1. Which classes have you taken, and what’s the typical class size (if it’s all on Zoom, how many students are in the meetings)? Have any courses stood out as your favorites?
  2. Is it difficult to secure electives (especially at Wharton)?
  3. NYU has a dedicated Center for Data Science that holds events like company info sessions, private career fairs, datathons, etc. How strong is the data science community at Penn, and how is the program viewed within the university? Are there similar events/services?
  4. On the topic of internships, has the school helped students secure these, and are most of you finding them in Philadelphia or elsewhere?
  5. Finally, do graduate students typically live off-campus or at Sansom Place? I think Rittenhouse Square may be my best option.

Thank you!

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9 hours ago, Sea Salt said:

Hey, @carolbells, thanks for the update! I’m glad that you’re enjoying Penn.

I have some questions if you don’t mind.

  1. Which classes have you taken, and what’s the typical class size (if it’s all on Zoom, how many students are in the meetings)? Have any courses stood out as your favorites?
  2. Is it difficult to secure electives (especially at Wharton)?
  3. NYU has a dedicated Center for Data Science that holds events like company info sessions, private career fairs, datathons, etc. How strong is the data science community at Penn, and how is the program viewed within the university? Are there similar events/services?
  4. On the topic of internships, has the school helped students secure these, and are most of you finding them in Philadelphia or elsewhere?
  5. Finally, do graduate students typically live off-campus or at Sansom Place? I think Rittenhouse Square may be my best option.

Thank you!

1) So far I've mostly taken classes required for all DATS students including Stats, Machine Learning, and Big Data Analytics. Electives so far include databases, forecasting analysis, and probability models in marketing. Classes have been online this school year. Since classes are recorded many people don't show for the live lectures but classes sizes highly depend on the classes you're taking. I say average is about 30-50. So far the most interesting class is Probability Models in Marketing - it's one of the most popular classes in Wharton and the professor is a really good orator. 

2) Depends on the particular class - the forecasting analysis class is in Wharton and pretty much everyone I knew who wanted to get into the class was able to get in. The probability models in marketing class is much harder to get into due to its popularity. They only allowed about 15 people outside of Wharton to get into the class. Usually it's not really a problem

3) There are company events that shared to all DATS students but from what I know, they aren't limited to only DATS students - anyone outside of the program can attend them as well. There's only about 50ish students in each year's cohort so we're a small bunch and it wouldn't make sense to only have programs for just us. There is the Data Science General Assembly, Wharton Analytics Fellows, Penn Data Science group, etc. that also allow students interested in DS to meet up. It's a bit hard to say how strong the community is due to the program being remote at the moment but I think it's pretty reasonable.

4) I personally got my internship on my own without anyone from Penn. I think most of my peers experienced the same. There are career fairs and stuff like that but ultimately the students are the ones who put in the effort to get the internships. I find that most of the companies at the career fairs are centered around the East Coast which I'm personally not interested in so I didn't pursue the pipelines that the school might have offered. Most of us found internships outside of Philly in places like Seattle, SF Bay Area, Boston, Chicago, etc.

5) I think everyone I know lives off campus - but usually only several blocks away. I don't know anyone who lives in Sansom place.

Hope this helps!

 

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Thought I should chime in with my results, although I'm def not in the same league as you guys haha. Got into UT Austin's Business Analytics, CMU's MISM in the Business Intelligence and Data Analytics Track, USF DS with a scholarship, and got waitlisted at NYU(I'm assuming there's almost no chance to get off this so in my mind this is a reject). 

Rejected from GATech MSiA and NU MSiA.

Not heard from Columbia DS yet so I'm assuming it'll either be a waitlist or rejection.

I'll likely be headed to CMU if I don't hear from Columbia soon. Let me know if you guys need any info on CMU/UT Austin/USF. I've researched their programs quite a bit.

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  • 2 weeks later...

@carolbells

Thanks for sharing! That's a lot of great info. I had heard of PDSG, but the Wharton Analytics Fellows group looks really interesting too.

How are you planning on structuring your last year? Full-time is 3 courses, but the whole program is 10. Are you thinking of taking 4 classes in the fall and finishing up in 1.5 years, or would you do 3+1 or 2+2?

Finally, are you considering doing the practicum? It looks like Penn has its data science students work on these individually rather than in groups, and the projects seem to have more of an academic than industry focus. Of their project suggestions, I would imagine most would involve collaborating with other Penn institutes. I'm not sure if any would entail working with outside companies.

edit: Btw, I was able to visit Penn recently. It has a really beautiful campus. There's a special feel to it.

Edited by Sea Salt
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@Sea Salt 

 Most people do 3+3 in Year 1 and 2+2 in year 2 (that's what I'm doing). There are several people who do something like 4+3 in year 1 and then 3 in the following Fall to graduate a semester early but this isn't very common 

I'm still debating on doing the practicum since there's lots of classes that I really want to take and doing a practicum would take time off of them. I think practicums are helpful when you don't have an internship lined up or something but if you do, I wouldn't stress about doing the practicum unless you really want to. Practicums are conducted within the university, I don't think you'd work with outside companies on it.

 

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3+3+2+2 sounds nice. I much prefer 2 full years. Penn is definitely one of my top choices, but I still like NYU's program, career services, practicum, and connections to NYC tech companies. GaTech is up there too, but it's more like 1.5 years, and it includes two required business classes. Their cohort size (~80) is tough to beat, however. I hear Penn will be anywhere from 50-150 students next year, and NYU will be 150+.

It'd be nice if Penn had their admitted students webinar sooner. It's set for May, after everyone else's deadline to commit. I doubt there's an old one accessible somewhere.

Anyway, @carolbells, thank you for the helpful information! I really appreciate you taking the time to write those thoughtful responses.

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Accepted:

  • UC Berkeley EECS M.Eng (Data Science and Systems concentration)

Pending:

  • Columbia MS Computer Science
  • Penn MSE Data Science

Rejected:

  • Harvard MS Data Science
  • Yale MS Statistics and Data Science

- Is anyone else still waiting to hear back from Columbia and Penn? I sent my application to Columbia on Jan 13 and Penn on March 5th. Haven't heard back from either, so I think it is safe to assume that I got rejected from both at this point? :[

- Also, anyone familiar with Berkeley EECS M.Eng program? I dont think I have seen anybody here applied to the program. I know that Berkeley's EECS department is ranked #1 in the country and that I'm looking for an engineering focused program. However, I still have a few reservations: mainly that it is only 1-year, which is relatively short and would not allow me to have a summer internship like a regular MS program (although I already had a few years of work experience, so not sure if an internship would be that impactful?). Also, the program recommends students taking only 4 technical courses (CS, ML, DS), while requiring 4 business leadership courses and 2 capstone research courses. I really want to take more than 4 technical courses lol.

- If anyone here is familiar with the program I would really appreciate your inputs :) 

Edited by HTP1234
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On 4/19/2021 at 9:38 AM, ny_gabby said:

@HTP1234 I also have not heard back from Columbia yet. From last year's forum on this topic I saw that some people were admitted all the way into May. 

When did you apply though? I applied on Jan 13 (before the first priority deadline) so it has been more than 4 months. I wonder what is taking them so long, maybe we are on an unofficial waitlist?

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