MATH 2310 - Linear Algebra for Data Science

(SMR-AS) (MQL-AG, OPHLS-AG)

Fall, Spring. 4 credits. Student option grading.

Forbidden Overlap: due to an overlap in content, students will receive credit for only one course in the following group: MATH 2210, MATH 2230, MATH 2310, MATH 2940.
Prerequisite: MATH 1106, MATH 1110, or equivalent AP credit. Students who have taken MATH 2310 may need more foundational coursework before pursuing further study in mathematics and should contact the director of undergraduate studies for advice before continuing. For guidance in selecting an appropriate course, please consult First Steps in Math.

Staff.

An introduction to linear algebra for students interested in applications to data science. The course diverges from traditional linear algebra courses by emphasizing data science applications while teaching similar concepts. Key topics include matrices as data tables, high-dimensional datasets, singular value decomposition for data compression, and linear transformations in computer graphics.