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CISC 351 Advanced Data Analytics Units: 3.00
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.
Learning Hours: 120 (36 Individual Instruction, 36 Laboratory, 84 Private Study)
Requirements: 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).
Exclusion CISC 371; CISC 372.
Offering Faculty: Faculty of Arts and Science