I am a Mechanical Engineer applying for Masters's in Financial Engineering program in the USA. I have around four years of experience in the field (Quantitative Modeling of Credit Products).
In general, I am interested in the mathematical aspects of this subject, and I have taken a few unsupervised reading projects, e.g., a self-study of Undergraduate Statistics from Casella and Berger (including exercises) and a Study on Brownian Motion Calculus.
For Machine Learning, I have taken two specialization courses on Deep Learning from Coursera and Udacity.
Over this period, I have expanded my knowledge base. I have recently been trying to ossify this learning by doing independent projects (preferably implementing an ML Concept in Option Pricing). I have found a few papers that employ MLPs for Pricing Options and Calibrating Volatility Surface.
Shall I include these learnings in my Statement of Purpose, especially since a large part of it is unsupervised? What steps can I take to ensure it comes off as authentic and credible?
I feel these learnings have vastly enhanced my interest and are one of the core reasons I wish to pursue further studies.