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) |