Engineering Management Graduate Certificate

Explores economic modeling and analysis techniques for selecting among engineering alternatives. Covers present worth, annual worth, rate of return, and benefit/cost methods. Examines decisions under uncertainty using sensitivity analysis, decision trees, expectation-variance criteria, and multiple attribute decision making.

Studies fundamental concepts of probability and statistics for engineering applications. Topics include random variables, common probability distributions (binomial, Poisson, normal, exponential), sampling, parameter estimation, confidence intervals, hypothesis testing, and analysis of variance.

Examines the theory and practice of managing projects. Explores human, mathematical, entrepreneurial, managerial, and engineering aspects of project management. The systems development life cycle is the framework for the course. Addresses needs analysis, requirements definition, design, and implementation in the context of project management. Introduces mathematical and software tools for planning, monitoring, and controlling projects.

Introduces the theory, computation, and application of deterministic models to represent industrial operations. Includes linear programming formulation and solution using spreadsheet and algebraic languages software; simplex, big-M, two-phase, revised simplex, and dual simplex algorithms for solving linear programs; introduction to the theory of simplex, fundamental insight, duality, and sensitivity analysis; transportation, assignment, and transshipment problems; shortest path, minimum spanning tree, maximum flow, minimum cost network flow problems and project networks; and discrete-state and continuous-state dynamic programming models and applications. Requires knowledge of linear algebra.