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  • ISE 4015 Management Systems Theory, Applications and Design (Fall)
    - Decision Analysis for Management Judgment
    - HBR Guide to Better Business Writing (HBR Guide Series)
    - HBR Guide to Persuasive Presentations (HBR Guide Series)
    - slide:ology: The Art and Science of Creating Great Presentations

    Course Description: The focus of this course is on the assessment, analysis, design, and improvement of management systems used to support organizational decision-making and improvement. A systems perspective and engineering approach is applied to the design and improvement of management systems. A manager needs to have tools that allow him or her to gauge the workplace and make decisions, resulting in actions that affect workplace performance. You will learn about decision-making concepts, including decision analysis and game theory. We will also talk about communications, professional writing and current topics of importance to practicing industrial engineers. This course helps you understand concepts and develop skills to better work with those who manage you, to better manage others, to design systems for management decision-making and to make better decisions.

  • ISE 5984 Decision and Risk Analysis (Spring)
    - Foundations of Decision Analysis

    Course Description: This course covers principles, methods and applications of decision analysis and risk analysis. Students will learn how to systematically formulate and solve decision-making and risk management challenges in an engineering context. The course will cover multicriteria decision-making, decision-making under uncertainty, group decision-making, game theory, the value of information and risk management techniques.

  • ISE 6054 Decision Theory (Fall)
    - Decisions with Multiple Objectives: Preferences and Value Tradeoffs
    - Advances in Decision Analysis: From Foundations to Applications

    Course Description: The focus of this course in on decision making, including normative (how people should make decisions), descriptive (how people make decisions) and prescriptive (helping people make better decisions) decision theory. You will be introduced to fundamental concepts and current research in decision analysis, utility theory, Bayesian inference / networks, behavioral and classic game theory, decision making models for hierarchical, distributed and multiscale systems. This course is targeted towards advanced Ph.D. students: one of the course objectives is to make a contribution to the academic literature; prior knowledge in probability theory is recommended.