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MS in Statistics, UChicago, Duke, or UCLA


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Hi All,

I am now deciding between these 3 offers for a MS in Statistics and would really appreciate your inputs. 

  My background: Undergrad in Math/Stats, 2 year full time work exp in Data Analytics. 

  Goal: Working on the application of advanced machine learning algorithms. Preferably in California.  


Pros: 1. overall reputation is probably the best (but I am not sure about this for Californians).

           2. Treated as PhD (research advisor, take classes together with PhD)

           3. Cost is reasonable (37k after 25% off, vs Duke 52k vs UCLA 31k)


Cons: 1. This program is highly theoretical. In the placement reports, not many people ended up as Data Scientists, and not many people went to California. Instead, many went to PhD programs. I am not sure if this is because the students in this program were not interested in industry or because it is hard to get DS jobs after graduating from this program.

            2. It is a very competitive program and the life there is stressful (from what I heard)

            3. Stats Dept. itself does not offer many advanced machine learning classes. Instead, students can take these classes from Toyota Technology Institute at Chicago (an independent ML research institute located in UChicago). I am not sure how feasible this is. 



Pros:  1. Best CA Data Scientist placement (about 50% graduates went to CA to work as DS in the past 2 years)

            2. Statistics courses covered most parts of the essential knowledge so no need to petition to enroll in other departments' classes. 


             1. Most expensive

             2. slightly less well-known than UChicago? 


Pros: 1. Cheapest

          2. Potential to transfer to PhD program after 1st year (I would not mind doing one if I find myself enjoy research, although the likelihood is low)

          3. LA, LA, LA. This will be a very important factor for job hunting if I want to land a job in CA. 


          1. The program's ranking is not among the first tier as the other 2 programs. 

           2. Not too many data points from past graduates on job placements. 


Thanks and I look forward to your comments and suggestions! 


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