Seminar in Data Sciences

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.

Measure Theory for Engineers

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

High-Dimensional Statistics

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.

The topology of 3-manifolds

Topics class offered in FALL 2021 by John Etnyre. 

Descriptive Combinatorics

Topics class offered in FALL 2021 by Anton Bernshteyn.

Spectral Graph Theory

Topics class offered in FALL 2021 by Zhiyu Wang. 

Spectral Graph Theory

Topics class offered in FALL 2021 by Zhiyu Wang. 

College Algebra

Study of the properties of algebraic, exponential, and logarithmic functions as needed for pre-calculus and calculus.

Probability Theory

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.

MATH 3215, MATH 3235, and MATH 3670 are mutually exclusive; students may not hold credit for more than one of these courses. 

Mathematical Problem Solving

Pass/Fail basis. This course is intended to teach general mathematical problem solving skills, and to prepare students to take the Putnam Examination.


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