DASC 32003 — Optimization Methods in Data Science
is an advanced mathematical course providing the foundations and concepts of optimization that are essential elements of machine learning algorithms in data science, ranging from mathematical optimization to convex optimization to unconstrained and constrained optimization to nonlinear optimization to stochastic optimization. Students will gain hands-on experience using Python and various optimization packages in Python. Corequisite: DASC 32103 . Prerequisite: DASC 21103 , DASC 25904 , ( DASC 310H3 or DASC 31003 ), (( MATH 30103 and STAT 30043 ) or ( INEG 23104 and INEG 23203 )), and student must be a DTSCBS major. (Typically offered: Spring)
Prerequisites: DASC 21103, DASC 25904, DASC 31003, MATH 30103, STAT 30043, INEG 23104, INEG 23203