Seminar series in which different groups within the College of Sciences will give talks about how their research
relates to data sciences and machine learning.
This course is a mathematical introduction to probability theory, covering random variables, moments, multivariate distributions, law of large numbers, central limit theorem, and large deviations.
This course will cover important topics in linear algebra not usually discussed in a first-semester course, featuring a mixture of theory and applications.