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Course Criteria
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3.00 Credits
This course surveys information-systems technology for the management of corporate information as a resource. Topics include elements of system design life cycle, database concepts, and Internet processing. Managerial and technical dimensions of information systems are blended in a framework of MIS. Projects are required. Prerequisites/Corequisites: Prerequisite: CSCI 1190 or equivalent. When Offered: Spring term annually. Credit Hours: 3
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4.00 Credits
his course surveys information-systems technology for the management of enterprise information as a resource. Topics include elements of system design life cycle, database concepts, and decision support. Managerial and technical dimensions of information systems are blended in a framework for IS systems. Additional topics include telecommunications, artificial intelligence (including expert systems), and structured design. The implementation, operation, and maintenance of information systems are also discussed. Projects are required. Students cannot obtain credit for this course and DSES 4510. Prerequisites/Corequisites: Prerequisite: CSCI 1190 or equivalent. When Offered: Fall term annually. Credit Hours: 4
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3.00 Credits
Development of basic approaches of deterministic operations research to decision problems. Focus on optimization algorithms. Introduction to linear, integer, binary integer and nonlinear programming. Genetic algorithms. Consideration of model formulation and implementation. Prerequisites/Corequisites: Prerequisite: MATH 1020 or equivalent. When Offered: Fall term annually. Credit Hours: 3
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3.00 Credits
Development of basic approaches of probabilistic operations research to decision problems. Focus on the formulation, estimation, and analysis of Markov, queuing, and discrete-event simulation models. Extensive use of computers. Prerequisites/Corequisites: Prerequisite: ENGR 2600 or equivalent. When Offered: Spring term annually. Credit Hours: 3
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4.00 Credits
Axioms of probability, joint and conditional probability, random variables, probability density and distribution functions, expectation, functions of random variables, and limit theorems. Applications of probability to models in operations research, including queuing theory and Markov chains. Prerequisites/Corequisites: Prerequisite: MATH 1020 or equivalent or permission of instructor. When Offered: Fall term annually. Cross Listed: Cross-listed as MATP 4600. Students cannot obtain credit for both this course and MATP 4600. Credit Hours: 4
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4.00 Credits
A course in the theory of statistics which will provide students with a basic foundation for more specialized statistical methodology courses. Topics include sampling and sampling distributions; point estimation including method of moments, maximum likelihood estimation, uniform minimum variance estimation and properties of the associated estimators; confidence intervals; hypothesis testing including uniformly most powerful, likelihood ratio approaches, chi-square tests for goodness-of-fit and independence. The course will conclude with an introduction to linear statistical models. Prerequisites/Corequisites: Prerequisite: DSES 4750 or MATP 4600 or equivalent calculus-based course. When Offered: Spring term annually. Cross Listed: Cross-listed as MATP 4620. Students cannot obtain credit for both this course and MATP 4620. Credit Hours: 4
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4.00 Credits
Introduction to deterministic models of operations research including linear programming formulations, the simplex algorithm, degeneracy, geometry of convex polyhedra, duality theory, and sensitivity analysis. Special linear programming models for assignment, transportation, and network problems. Integer programming formulations along with branch and bound solution. Dynamic programming. X Prerequisites/Corequisites: Prerequisites: MATH 1020 and MATH 2010 or ENGR 1100 or equivalent, or permission of instructor. When Offered: Fall term annually. Cross Listed: Cross-listed as MATP 4700. Students cannot obtain credit for both this course and MATP 4700. Credit Hours: 4
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4.00 Credits
An introduction to nonlinear programming. Models, methods, algorithms, and computer techniques for nonlinear optimization are studied. Students investigate contemporary optimization methods both by implementing these methods and through experimentation with commercial software. Nonmajors wishing to gain practical optimization skills are welcome in this course. A course project allows students to explore optimization methods and practical problems directly related to their interests. Prerequisites/Corequisites: Prerequisites: MATP 4700 or DSES 4770, and MATH 2010 or ENGR 1100, and CSCI 1100, or equivalent, or permission of instructor. When Offered: Spring term annually. Cross Listed: Cross-listed as MATP-4820. Students cannot obtain credit for both this course and MATP-4820. Credit Hours: 4
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3.00 Credits
With ever-increasing computer power readily available, new engineering methods based on "soft computing" are emerging at a rapid rate. This course provides students a working knowledge in computational intelligence covering the basics of fuzzy logic, neural networks, genetic algorithms, simulated annealing, wavelet analysis, fractal structures, and chaotic time series analysis. Applications in control, optimization, data mining, fractal image compression, and time series analysis are illustrated with engineering case studies.When Offered: Spring term annually. Credit Hours: 3
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1.00 - 6.00 Credits
Credit Hours: 1 to 6
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