Skip to main content

MATH 221 Mathematics for Data Science

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
4 Undergraduate credits

Effective January 1, 2019 to present

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