16:640:640 Experimental Math

Spring 2020

Doron Zeilberger


Bayesian Reasoning

Course Description:

Experimental Mathematics used to be considered an oxymoron, but the future of mathematics is in that direction. In addition to learning the philosophy and methodology of this budding field, students will become computer-algebra wizards, and that should be very helpful in whatever mathematical specialty they are doing (or will do) research in.

We will first learn Maple, and how to program with it. This semester we will learn, from an experimental mathematics point of view, the very important topic of Bayesian Probability, so important in machine learning and data science, as well as algorithmic gambling.

This class takes place in the computer lab at ARC in an IML room.


Handouts and internet resources