UChicago MSFM vs NYU MFE vs UCLA MFE

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So, I recently got through these 3 programs and I am still waiting on decisions from a couple others. Can someone please explain if there are any reasons to go to UCLA/NYU over UChicago? I am hoping to focus on ML through my program, and looking for trading roles over research roles post-graduation (open to both).
 
Personally I'd take Chicago all day over Tandon and UCLA, especially with a big scholarship.

It depends on a multitude of factors though (where you want to work, what your current strengths and weaknesses are, etc.)
 
Personally I'd take Chicago all day over Tandon and UCLA, especially with a big scholarship.

It depends on a multitude of factors though (where you want to work, what your current strengths and weaknesses are, etc.)
Not the OP, but why would current strengths and weaknesses affect the choice?
 
Not the OP, but why would current strengths and weaknesses affect the choice?
My thought process was that variance in curriculums make it so specific programs cater better to people with specific backgrounds.

For example compare Chicago's curriculum with UCLA's. If I come from a strong math and finance background but want to develop my programming skills, I think I'd fair much better in Chicago. Also note that UCLA teaches in Python and R while Chicago teaches some of their courses in c++
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My thought process was that variance in curriculums make it so specific programs cater better to people with specific backgrounds.

For example compare Chicago's curriculum with UCLA's. If I come from a strong math and finance background but want to develop my programming skills, I think I'd fair much better in Chicago. Also note that UCLA teaches in Python and R while Chicago teaches some of their courses in c++ View attachment 51387View attachment 51385
UCLA should drop their "Balancing Purpose and Profit". Kinda lame spending thousands of dollars and precious time on courses like those. Everyone knows it's greenwashing. What really matters for "sustainability" (both economically and socially) is not making mistakes and try to cut corners, exposing one's company to legal problems. Otherwise, it's just bs (specially the "dversity" thing). Companies really need smart people, not "diverse people".
 
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