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This course introduces the foundations of discrete mathematics as they apply to computer science, focusing on providing a solid theoretical foundation for further work. Topics include functions, relations, sets, simple proof techniques, Boolean algebra, propositional logic, elementary number theory, writing, analyzing and testing algorithms.

This course introduces the foundations of discrete mathematics as they apply to computer science, focusing on providing a solid theoretical foundation for further work. Topics include functions, relations, sets, simple proof techniques, Boolean algebra, propositional logic, elementary number theory, writing, analyzing and testing algorithms.

The study of different types of optimization problems arising in different fields of business and industry. Examples are provided on sensitivity analysis of parameters of a model and calculating shadow prices. Course Avatar and Header Image created at logomakr.com

The study of different types of optimization problems arising in different fields of business and industry. Examples are provided on sensitivity analysis of parameters of a model and calculating shadow prices. Course Avatar and Header Image created at logomakr.com

The use of discrete and continuous distributions to construct deterministic and stochastic simulation models. Stochastic simulations may include Markov Processes, M/G/1 Queuing Systems, Monte Carlo Simulation and Analytic Simulation.

The use of discrete and continuous distributions to construct deterministic and stochastic simulation models. Stochastic simulations may include Markov Processes, M/G/1 Queuing Systems, Monte Carlo Simulation and Analytic Simulation.