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CISC 371 Nonlinear Data Analysis

CISC 371  Nonlinear Data Analysis  Units: 3.00  

Methods for nonlinear data analysis, particularly using numerical optimization. Applications may include: unconstrained data optimization; linear equality constraints; constrained data regression; constrained data classification; evaluating the effectiveness of analysis methods.

Learning Hours: 120 (36 Lecture, 84 Private Study)  
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in (CISC 271 and [STAT 263 or STAT_Options]). Exclusion CISC 351.  
Offering Faculty: Faculty of Arts and Science