MATH 300
Mathematical Methods for Data Science
New York Institute of Technology · UGRD · Fall 2026
1 section
Catalog description
This course immerses students in computational mathematics with applications to data science through hands-on coding projects and written reports. Topics for the course include polynomial interpolation, least-squares fitting, cubic splines, numerical optimization, data dimension reduction, logistic regression, methods of data classification and supervised machine learning. Prerequisite Course(s): Prerequisites: MATH 260. Corequisites: MATH 310. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3
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Availability not recently verifiedClass #new_york_2-MATH300Fall 2026UGRD3.0 credits
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