Data Analytics. (3-0) 3 Credit Hours

Catalog description

Prerequisite: MAT 1214 , MAT 2233 , and MAT 4113 or CS 1063 or CS 1083 or CS 1093, or equivalent, or consent of instructor. This course is intended to develop practical marketable skills in data analytics using rigorous mathematical methodologies via SQL, Python, and Git. The mathematical topics covered involve: Singular value decomposition, single and multiple discriminant analysis, integral transforms with orthogonal and non-orthogonal functions/data and their connection with regression techniques, and nonlinear discriminants through dimensionality augmentation (artificial neural networks). The course covers techniques to characterize the context of a data problem, and addresses issues related to reproducibility of computational results. (Same as MAT 4153 . Credit can not be earned for both MAT 4153 and MAT 5153 .) This course has Differential Tuition. Course Fee: GS01 $90.