Course: STAT 24320
Title: Applications in Numerical Linear Algebra
Instructor(s): Kendra Burbank
Teaching Assistant(s): TBA
Class Schedule: Sec 1: MW 1:30 PM-2:50 PM in Saieh 141
Description: This course delves into the practical applications of methods in numerical linear algebra. Students will see how material first introduced in STAT 24300 can be applied to problems in data analysis, dynamical systems, and statistics. Topics will include projection and orthogonality for optimization in linear systems; spectral methods for discrete time dynamical systems and sampling algorithms including Markov Chain Monte Carlo; and matrix decompositions such as QR and SVD for dimensionality reduction techniques including PCA and others. For each topic, students will have multiple opportunities to apply the methods to real data sets. While this course will not emphasize programming, some familiarity with Python or Julia is encouraged.