Description
Design and implementation of complex analytics techniques; predictive algorithms at scale; deep learning; clustering at scale; advanced matrix decompositions, analytics in the Web, collaborative filtering; social network analysis; applications in specialized domains.
Follow-On Courses
This course appears in the pre- or co-requisites for the following course(s):
Learning Hours
120 (36 Individual Instruction, 36 Laboratory, 84 Private Study)
Prerequisite
A minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in CISC 251 and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (3 units in STAT or 3 units from STAT_Options).