To whom it may concern,
A personal statement is not mandatory for my application to a Masters in Analytics but is an opportunity for me to advertise my interest and relevant experience. This letter will comprise a quasi-biographical form since that is the easiest medium for expressing and communicating my position.
I have a background in biomedical science (completed with an Honours year in 2008, and going to begin but not finish a PhD in the fields of cell signalling and neurodegeneration). Illness interrupted my studies, which planted the seeds for apathy and depression. I skip this part of the story.
I began reinvigorating myself with a purpose in 2015, and by November of that year decided that whatever I would want to do, it would have to involve computers. Being unfamiliar with programming, yet enamoured by the obvious potential of iterative processes, I began a quest for self-study.
This auto-didactic curriculum has thoroughly meandered, but as I learned more I honed my focus, until such time as I knew without a doubt that my passion lay in data science.
I am passionate about my potential for learning data science, and in time applying those skills in the domains of biological research.
This brings me to the current day. In order to indicate a sense of my journey over the last 5 months, I have attempted a summary (necessarily incomplete) of areas of study, and resources of inspiration.
- Learning python fundamentals – Codacademy and Learn Python the Hard Way
- Producing a card war game utilizing Pygame (GUI) and a message queue system – by way of The Python Game Book, Foundations in Python Networking
- Learning to implement web frameworks (Flask), deployment (Heroku), and SQL (Flask-Alchemy, Postgres) – by way of multiple web resources, including those by Miguel Grinberg
- Many Pycon (python conference and workshop) talks available on youtube
- Learning R fundamentals – Cousera courses The Data Scientists Toolbox and R Programming and Getting and Cleaning Data, and the book R Programming for Data Science by Peng
- Refamiliarizing myself with maths by way of Khan Academy, working through their “missions” on trigonometry, pre-calculus, differential calculus, and integral calculus
- Inspiring myself with a handful of podcasts that discuss data science and machine learning
It is difficult to communicate an impression, but I hope that I have given you a sense of my journey, purpose, and sense of discovery, and thus also of my passion.
Yours sincerely,
Shai Marom
