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Optimization And Prescriptive Models (DSC-784)

Semester:	Summer 2022
Number:	0207-784-001
Instructor:	TBA
Days:	Tuesday Thursday 6:00 pm - 9:00 pm
Note:	Online, Synchronous
Location:	Online
Credits:	3
Course Meets:	May 26 - July 1
Course Materials:	View Text Books
Related Syllabi:	Jared Mroz for Spring 2024*
	*Attention Students: Please note that the syllabi available for your view on these pages are for example only. The instructors and requirements for each course are subject to change each semester. If you enroll in a particular course, your instructor and course outline may differ from what is presented here.
Description:	Students will be introduced to the basic concepts, principles, and techniques of decision modeling and analytics. The first part of the course focuses on the use of optimization to support decision-making in the presence of alternatives and business constraints. The second part focuses on the use of Monte Carlo simulation.
Learning Goals:	Upon completing the course, Students will: • Understand the scope of management problems that can be addressed with decision models; and learn to identify opportunities for creating value using decision models; • Develop models that can be used to improve decision making within an organization; • Sharpen their ability to structure problems and to perform logical analyses; • Practice translating descriptions of decision problems into formal models, and investigate those models in an organized fashion; • Recognize the types of modeling tools most adapted to a given situation; • Know how to assess the significance of model outputs for managerial insights and action; • Strengthen their computer skills, focusing on how to use the computer to support decision-making. *The learning goals displayed here are those for one section of this course as offered in a recent semester, and are provided for the purpose of information only. The exact learning goals for each course section in a specific semester will be stated on the syllabus distributed at the start of the semester, and may differ in wording and emphasis from those shown here.

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