I got the MIT MicroMaster in Statistic and Data Science :-)

Just happy I passed today the Capstone Exam for the MIT(x) MicroMaster in Statistics and Data Science.

Very rewarding program! (conversy, the exam proctoring software was terrible)

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In the description they state:

  1. “…college-level calculus and comfort with mathematical reasoning and Python programming are highly recommended if you want to excel.”
  2. “…use python and R skillfully to analyze data.”

Is it possible to work through this program using Julia exclusively or is it necessary to use Python/R?

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Never use the word Excel in any way associated with data analysis :slightly_smiling_face:

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In short: It is not really a program about programming :slight_smile:

I was in your situation, where I wasn’t particularly interested in R/Python.
However there is very little of programming. In the Data Science course there is a little bit of R to show some methods, but that’s all.
Even less for Python in the ML course. Python is there because there isn’t ML without the computational aspects (and, I guess, to attract the masses…), but it always remains secondary and the capstone exam had no questions requiring Python. It’s all about ML concepts and algorithms in analytical form (altought the projects do require very minimal python).

Personally I enployed Julia all across the program, mainly to better understand the concept taught.
I also created a Package that started from implementing in Julia the main ML algorithms presented, in the ML GitHub - sylvaticus/BetaML.jl: Beta Machine Learning Toolkit BetaML.

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