UCLA vs UF vs Texas A&M

[anon333]

Hello,

Can people give me their opinions/ranking on any of the schools (Statistics PhD):

UCLA, UF, Texas A&M

I've been admitted into these schools, and I'm having hard time deciding...

 

My opinion:

UCLA

-seems good for industry jobs (i.e. data science), since located in LA

-course load seems heavy on machine learning (good)

-expensive to live in though (apartment/food worries...)

UF

-course load seems to be more oriented toward traditional statistics (no machine learning courses)

-I heard they're theoretical heavy (good)

-located in my hometown (wouldn't have to worry about life stuff, i.e. cost of living, food, etc.)

Texas A&M

-I heard they're a very large department that does mostly applied stuff

-I'm not that worried about the cult life thing

 

Bio:

-Undergraduate: UNC Chapel Hill, Graduating in May 2017 with Bachelors in Stats, Math

-US Citizen

-Hoping more for industry than academic job

 

Thank you so much!

Edited March 21, 2017 by anon333

[StatsG0d]

A&M has a pretty solid track record of placing into academia and industry, so in case you change your mind, it might be the best option. UCLA does have a great program and a few people working on machine learning, so if you're absolutely positive about industry, I would consider there. Florida, as you say, is more of a traditional program and actually places very well in academia relative to its ranking. The industry placements I would say are just okay. George Michailidis at UF does some machine learning work, so while they may not have traditional coursework, the option to do ML work still exists. However, as I understand it, he is still supervising (remotely) several students at Michigan, and he already has quite a few students at Florida, so I don't think he'd really be able to spare a lot of time.

[Stat Assistant Professor]

While there are not any current machine learning courses offered in the Statistics Department at University of Florida, there is active research being done in the area of machine learning -- namely in the areas of network analysis, feature/variable selection, graphical models, and Bayesian nonparametrics, A lot of it is theoretical machine learning though, so if that's your thing, then UF is a good choice. 

Additionally, the Statistics Department at UF is hiring a lot of new professors in the coming years who are affiliated with the newly opened Informatics Institute. So I expect there will be even more opportunities for ML at UF in the upcoming years. 

Just my two cents.

[Ytluo]

Congratulations! I think all of three are good programs! Could I ask which program have you decided to go?