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CMOR 303

MATRIX ANALYSIS FOR DATA SCIENCE

Credit Hours: 3 · Undergraduate Upper-Level

Solution of linear systems and linear least squares problems. Eigenvalue problem and singular value decomposition. Introduction to gradient based methods. Applications to data science. Recommended Prerequisite(s): ( MATH 212 or MATH 222 ) and (CAAM 210 or CMOR 220 or COMP 140 or STAT 405 )

Prerequisites & course information

Short Title: MATRIX ANALYSIS DATA SCIENCE Department: Comp Appl Math Operations Rsch Grade Mode: Standard Letter Course Type: Lecture Distribution Group: Distribution Group III Credit Hours: 3 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level

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