MS3128 - Managerial Decision Analytics | ||||||||||||
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| * The offering term is subject to change without prior notice | ||||||||||||
Course Aims | ||||||||||||
This course aims to train students' skills in modelling and optimization that are essential in turning real-world business decision-making problems into mathematical models and developing solution methods using computer packages such as Python and Gurobi. It serves as a foundation course for business analytics, and covers commonly used optimization methods in business applications, including linear programming and nonlinear optimization. It also introduces application of the optimization methods to a wide range of problems, including statistical estimation, machine learning, and business decision making under uncertainty.?? | ||||||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||||||
Continuous Assessment: 40% | ||||||||||||
Examination: 60% | ||||||||||||
Examination Duration: 2 hours | ||||||||||||
Examination - The examination will assess the students' ability to select and apply the optimization concepts and methods to solve business problems, and to interpret the implications of optimization concepts in real-world decision making. | ||||||||||||
Detailed Course Information | ||||||||||||
| MS3128.pdf | ||||||||||||
