Master's of Science in Data Science

Graduation cap

Originally, I planned to do a Master's of Science in the field of Biochemistry after I finished my Bachelor's. I hoped to eventually work with developing a biopolymer that microorganisms can produce for us - something biodegradable, cheap and that would reduce our dependence on petroleum.

However, after visiting PyData Berlin in 2018 and learning a lot about data science, I became absolutely fascinated. I did a full 180 and now want to have a Master's in data science. As a stepping stone, I made my bachelor thesis a combination of both these fields.

I took the GRE and applied to five different universities - Harvard, Stanford, Columbia, NYU and the University of Rochester - and got in NYU and UofR! I chose to go to NYC instead of Rochester for several different reasons. I started my MSc in the fall of 2019!

Here's a short summary of my grades so far:

Class Grade
Intro to Data Science A
Probability and Statistics for Data Science A
Optimization and Computational Linear Algebra A-
Big Data A
Machine Learning A
Deep Learning (Pass)
Capstone Project
Computer Vision
Bayesian Machine Learning ()
Independent Research
Predictive Modeling with Sports Data (Planned)
Tools and Techniques for Machine Learning (Planned)