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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 provides students with a broad exposure to areas of mathematics research through weekly speakers.
Pass/Fail basis. This course is intended to teach general mathematical problem solving skills, and to prepare students to take the Putnam Examination.
Introduction to probability, probability distributions, point estimation, confidence intervals, hypothesis testing, linear regression and analysis of variance.
This course will cover important topics in linear algebra not usually discussed in a first-semester course, featuring a mixture of theory and applications.
Mathematical logic and proof, mathematical induction, counting methods, recurrence relations, algorithms and complexity, graph theory and graph algorithms.
An introduction to proofs in advanced mathematics, intended as a transition to upper division courses including MATH 4107, 4150 and 4317.
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.
Scientific computational algorithms on vector and parallel computers. Speedup, algorithm complexity, interprocesses communication, synchronization, modern algorithms for linear systems, programming techniques, code optimization.
Fourier series, Fourier integrals, boundary value problems for partial differential equations, eigenvalue problems
Georgia Institute of TechnologyNorth Avenue, Atlanta, GA 30332Phone: 404-894-2000