Description
Computational methods for artificial intelligence, 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.
Follow-On Courses
This course appears in the pre- or co-requisites for the following course(s):
Learning Hours
120 (36 Lecture, 84 Private Study)
Prerequisite
Registration in a School of Computing Plan and a minimum grade of C- in CISC 271/3.0 and a minimum grade of C- in (STAT 263/3.0 or 3.0 units from STAT_Options).