MATH 588 - Stochastic Analysis

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Description

Hours: Three hours lecture per week Prerequisites: Admission to the Computer Science or Mathematics Graduate Program Topics include: Brownian motion, stochastic integrals, conditional expectation, Kolmogorv's Theorem, applications of Lebesgue Dominated Convergence Theorem. Introduction to Stochastic Differential Equations will be given.

Units: 3.00
Grading: Letter Grade

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Session Section Class # Type Days Time Location Instructor Course Details [Key]
E1 1 2637 LEC T  6:00 PM  -  9:00 PM  Bell Tower 1688 Jorge Garcia Course Open Class Details Extended University Class In Person Class

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