COR Required Courses

These are the core COR courses.

The following courses are required. Recommended electives that count toward the 30 credit requirement only can be found here.

Math 551. Probability. Fall and Spring [3] Prerequisite(s): Consent of instructor.
Topics include: combinational analysis, discrete and continuous probability distributions and characteristics of distributions, sampling distributions.

Math 524. Operations Research II---Stochastic Models. Spring [3]. Pre-requisite: Math 551 or equivalent probability background. A survey of probabilistic Operations Research models and applications. Topics include stochastic processes, Markov chains, queueing theory and applications, Markovian decision processes, inventory theory, and decision analysis.

COR 606. Computing Methods. Fall [3]. Experience with programming languages R and C, Linux operating system, Linux editors (e.g. vi, pico, gvim), AMPL modeling language, LaTeX and Beamer.

COR 628. Linear Programming. Fall [3]. Pre-requisite: Equivalent of Math 211. Co-requisite: Equivalent of Math 241. Theory and applications of linear programming. Topics include the simplex method, duality theory, sensitivity analysis, and interior point methods. Problems will be solved using appropriate software tools.

COR 696. Introduction to Simulation. Fall [3]. Pre-requisites: Equivalent of Math 451 and CSci 241. Simulation model building in a high-level simulation language (SIMAN) with C++/C interface. Topics include network, discrete-event, and continuous modeling approaches. Interfaces between the three modeling approaches are presented. Familiarity with univariate and multivariate probability distributions is required for input modeling and simulation output analysis. Course culminates in a semester project in SIMAN.