AI and Machine Learning — UChicago

An eight-week Artificial Intelligence and Machine Learning course at the University of Chicago covering the mathematical and theoretical background for machine learning in today's business world — from data investigation and exploration to supervised and unsupervised learning.

The final project developed a quantitative trading strategy for Real Estate Investment Trusts (REITs) that leverages machine learning, sentiment analysis, and time series analysis to identify undervalued REITs within specific sectors and sub-sectors. The strategy uses market data from FactSet, sentiment analysis on REITs, and historical price data to make informed investment decisions, achieving superior risk-adjusted returns.