MATH-242 Applied Linear Algebra with Graph Theory
Fall for 2017-2018
Mueller, Graham
This course will focus on computational applications of linear algebra and graph theory to diverse problems such as encryption and decryption, audio and image compression, Google's PageRank algorithm, the Netflix Contest, and social network analysis. The material covered will be beneficial to students interested in learning applications of linear algebra and graph theory to problems of increasing importance in technology settings, such as the emerging field of data science. Experience with scientific computing, such as Matlab or Octave, or Python's numpy and scipy libraries will be useful, but is not required.

Textbook: Coding the Matrix, by Philip N. Klein, Newtonian Press, 2013.
Credits: 3
Prerequisites: Math-150
Other academic years
There is information about this course number in other academic years:
More information
Look for this course in the schedule of classes.

The academic department web site for this program may provide other details about this course.