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Independent research conducted under the guidance of a faculty member.
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.
Special topics course offered in Fall 2022 and Fall 2021 by Christopher Heil.
This course can be taken in place of MATH 6337, Real Analysis, to satisfy the prerequisite for MATH 6241, Probability I.
This course cannot be used for credit at the same time as MATH 6337
The goal of this PhD level graduate course is to provide a rigorous introduction to concepts and methods of high-dimensional statistics
having numerous applications in machine learning, data science and signal processing.
Topics class offered in FALL 2021 by John Etnyre.
Topics class offered in FALL 2021 by Anton Bernshteyn.
Topics class offered in FALL 2021 by Zhiyu Wang.
Study of the properties of algebraic, exponential, and logarithmic functions as needed for pre-calculus and calculus.
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.