Description
Elements of linear algebra for data analysis, including: solution of linear equations; vector spaces; matrix decompositions; principal components analysis; linear regression; hyperplane classification of vectorial data.
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
Level 2 or above and a minimum grade of a C- (obtained in any term) or a 'Pass' (obtained in Winter 2020) in {[CISC 101 or CISC 110 or CISC 151 or CISC 121] and [MATH 110 or MATH 111 or MATH 112] and [MATH 120 or MATH 121 or (MATH 123 and MATH 124) or MATH 126]}.