MATH 2310 — Linear Algebra for Data Science
General Information
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. Students who take MATH 2310 may need more foundational coursework before pursuing further study in mathematics.
Full Cornell course description (FA26)
Credits: 4
Prerequisites and Enrollment
Prerequisites: MATH 1106 or MATH 1110.
Forbidden overlaps: MATH 2210, MATH 2230, MATH 2310, MATH 2940
Recorded Offerings
| Semester | Listed instructors | Course details |
|---|---|---|
| Fall 2026 | Yunan Yang | Roster / syllabus |
| Spring 2026 | Yunan Yang | Roster / syllabus |
Workload and General Advice
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Course information checked against Cornell’s Spring and Fall 2026 rosters on September 18, 2026. The listed semesters are verified examples, not a complete offering history.