MATH 221
Spring 2020
 Section:
01
02

Certificates: Applied Data Science 
Course Cluster: Data Analysis Minor 
This is a course in the algebra of matrices and Euclidean spaces that emphasize the concrete and geometric. Topics to be developed include solving systems of linear equations; matrix addition, scalar multiplication, and multiplication; properties of invertible matrices; determinants; elements of the theory of abstract finite dimensional real vector spaces; dimension of vector spaces; and the rank of a matrix. These ideas are used to develop basic ideas of Euclidean geometry and to illustrate the behavior of linear systems. We conclude with a discussion of eigenvalues and the diagonalization of matrices. 
Credit: 1 
Gen Ed Area Dept:
NSM MATH 
Course Format: Lecture  Grading Mode: Graded 
Level: UGRD 
Prerequisites: None 

Fulfills a Major Requirement for: (ASTR)(CADS)(COMP)(DATAMN)(MATH)(MB&B)(NS&B)(PHYS) 

Past Enrollment Probability: 50%  74% 
SECTION 01 
Instructor(s): Pollack,David Times: ..T.R.. 02:50PM04:10PM; Location: TBA 
Total Enrollment Limit: 40   SR major: 0  JR major: 0   
Seats Available: 40  GRAD: X  SR nonmajor: 0  JR nonmajor: 0  SO: 15  FR: 25 
