OIT 604: Data, Learning, and Decision-Making
Spring 2020
The aim of this course is to cover modern tools for data-driven decision making. Most decision making tasks involve uncertainty that is directly impacted by the amount and complexity of data at hand. Classical decision models rely on strong distributional assumptions about the uncertain events. But in recent years, and due to growing availability of rich data, there has been a rapid adoption of models from machine learning and statistics that provide more accurate and personalized picture of the uncertainty which in turn leads to better decisions. The interplay between the multiple objectives of modeling the data, personalization, and decision optimization has created a number mathematical models that the course aims to cover.