MATH 221

Mathematics for Data Science

4 Undergraduate credits
Effective January 1, 2019 – Present

Graduation requirements this course fulfills

This course covers selective topics in calculus and linear algebra for data science. Course topics are functions, function transformations, limits, derivatives, integrals, matrices, matrix operations, determinant, transpose and inverse, systems of linear equations, eigenvalues, eigenvectors and eigenspaces. This course focuses on applications of those topics.

Special information

Note: Students whose prerequisites are not identified by the system should contact the Math and Statistics department for an override at

Learning outcomes


  • Describe function transformations
  • Calculate and apply derivatives for single variable functions
  • Calculate and apply calculate integrals for single variable functions
  • Perform matrix operations for data science application
  • Calculate eigenvalues and eigenvectors