Fall 2018

## 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.

## Undergraduate Seminar

Pass/fail basis.

This course provides students with a broad exposure to areas of mathematics research through weekly speakers.

## 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.

## Probability and Statistics with Applications

Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression and analysis of variance.

## A Second Course on Linear Algebra

This course will cover important topics in linear algebra not usually discussed in a first-semester course, featuring a mixture of theory and applications.

## Introduction to Discrete Mathematics

Mathematical logic and proof, mathematical induction, counting methods, recurrence relations, algorithms and complexity, graph theory and graph algorithms.

## Foundations of Mathematical Proof

An introduction to proofs in advanced mathematics, intended as a transition to upper division courses including MATH 4107, 4150 and 4317.

## Introduction to Graduate Mathematics

This course includes topics on professional development and responsible conduct of research. The course satisfies the GT RCR Academic Policy for Doctoral Students to complete in-person RCR training.

## Vector/Parallel Scientific Computing

Scientific computational algorithms on vector and parallel computers. Speedup, algorithm complexity, interprocesses communication, synchronization, modern algorithms for linear systems, programming techniques, code optimization.

## Classical Mathematical Methods in Engineering

Fourier series, Fourier integrals, boundary value problems for partial differential equations, eigenvalue problems