Catalog Course Search Details

 Department:    CS

 Course #:    171

 Credits:    5

 Variable:     No

 IUs:    5

 CIP:    11.0701

 EPC:    CSACSBS

 REV:    2024

 Course Description  

This course uses a high-level programming language as a vehicle to discuss aspects of linear algebra that are important in data analytics. Develop an understanding of how to use linear algebra to solve problems. Topics include basic matrix operations, linear transformations, ranges, linear combinations and spans, systems of linear equations, symmetric matrices, inverses, determinants, triangular matrices, trace, eigenvalues and eigenvectors.

 Prerequisite  

Prerequisite: CS 121 with grade C or higher or department chair permission.

Contact Hours (based on 11 week quarter)

Lecture: 55

Lab: 0

Other: 0

Systems: 0

Clinical: 0

Intent: Distribution Requirement(s) Status:  

Academic N/A  

Equivalencies At Other Institutions

Learning Outcomes

After completing this course, the student will be able to:

1. Solve problems using concepts and methods of linear algebra including topics such as Gauss-Jordan elimination, vector spaces, eigenvalues, eigenvectors, vector spaces, linear transformations.
2. Apply linear algebra concepts to common engineering and mathematical problems.
3. Write a program using linear algebra to solve an appropriate data analytics problem.
4. Describe the relationship between computer-based activities and application of linear algebra concepts.
5. Identify possible uses of linear algebra in various career fields.

General Education Learning Values & Outcomes

Revised August 2008 and affects outlines for 2008 year 1 and later.

Course Contents

1. Concepts and methods of linear algebra including topics such as Gauss-Jordan elimination, vector spaces, eigenvalues, eigenvectors, vector spaces, linear transformations.
2. Linear algebra concepts to common engineering and mathematical problems.
3. A program using linear algebra to solve an appropriate data analytics problem.
4. The relationship between computer-based activities and application of linear algebra concepts.
5. Possible uses of linear algebra in various career fields.