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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
Computing, Mathematics and Analytics – Specialization (Computing) – Bachelor of Computing (Honours)
...477 . ii. Data Analysis: CISC 271 ; CISC 371 ; CISC 372 ; CISC 473 ; STAT 361 ; STAT...
Computing, Mathematics and Analytics – Specialization (Computing) – Bachelor of Computing (Honours)
...477 . ii. Data Analysis: CISC 271 ; CISC 371 ; CISC 372 ; CISC 473 ; STAT 361 ; STAT...
Concurrent Education Degree Requirements
https://www.queensu.ca/academic-calendar/education/concurrent-education-program/degree-requirements/
...3.0, CISC 102 /3.0, CISC 203...303 /3.0, DRAM 371 /3.0, DRAM...