Review the course description and learning objectives which can be found in your syllabus and in this course header. What are your expectations for this course? Are there areas you feel more confident? Discuss with the class.

Course - Future Decision-Making & Management Science

Course Description

Utilizing spreadsheet software, this course helps students take full advantage of the power of spreadsheet modelling. Modelling is integrated into areas of business such as finance, marketing, and operations management. This course blends theory with real examples and real data. Applied learning and theory provide a solid foundation followed by practical, hands-on exercises. Students will learn @RISK and Precision Tree add-ins and how to incorporate "Big Picture" diagrams of spreadsheet models and data mining. Management decisions will be explored, based out information obtained by these methods.

Course Objectives

Students will learn quantitative modelling to help companies make better decisions and improve performance. By using quantitative Business Analytics methods - data analysis, optimization, simulation, prediction, and others - students could help companies improve business performance.

Student Learning Objectives (SLO)

By the end of the course, students will demonstrate the ability to:

1. Describe and apply the Linear Programming Model, network model, integer programming model, and non-linear programming model to specific situations.
2. Analyse decision problems to solve uncertainty.
3. Utilize data mining to discover patterns, trends, and relationships among data.
4. Apply effective decision making based on quantitative analysis.
5. Filter through complexity of data to determine what information is valuable in decision making.