MATH 391 - Topics in Analysis

Credits: 3

Prerequisite: MATH 311. Topics vary but can include complex analysis, topology, differential equations, differential topology, numerical analysis, functional analysis, measure theory, fractal geometry, Lebesgue integration and Fourier analysis, harmonic analysis, and analytic number theory. May be repeated for degree credit if the topic is different.

Fall 2021, MATH 391A-01: Topics in Analysis: Numerical Mathematics for Data Science (3). Prerequisite: MATH 311. This course is designed to introduce knowledge of numerical computation and analysis, in order to equip students with necessary numerical techniques to address practical questions arising from data science and other fields. We will discuss useful methods to construct mathematical models from given data and powerful algorithms to solve large scale systems of linear equations which are formulated during the creation of mathematical models. Students will also learn computational complexity, accuracy, stability, conditioning, and other mathematical concepts of numerical analysis which are fundamental in developing an efficient numerical algorithm. MATLAB will be the programming language used for this course. Wang.