Business Analytics
The course develops modelling skills for management contexts, for example finance, logistics, workforce scheduling, marketing, IT infrastructure and energy.
Appropriate quantitative methods will be introduced with spreadsheet applications and case studies. The methods include linear and integer programming, network models, multi-period models, goal programming, simulation and project management.
In this course, you will learn how to:
- Develop mathematical models to analyse complex business situations.
- Implement mathematical models in appropriate software, e.g., Excel, GAMS, or Python, to solve business cases.
- Test the validity of the model’s assumptions by performing sensitivity analysis and interpreting the findings.
Application areas include defence, energy, environment, finance, human-resource management, IT planning, logistics, manufacturing, marketing and transport.
Quantitative methods such as linear programming (LP), integer programming, network flows, multi-criteria analysis, and simulation will be applied as appropriate with an emphasis on problem formulation and computational implementation with realistic data.
This course is designed to develop your problem-solving skills and expertise in state-of-the-art decision tools. The emphasis will be on understanding the models thoroughly so that they may be applied to analyse real-world business decisions.
As always, while a mathematical approach is encouraged throughout, the main concepts will be illustrated through extensive case studies. Furthermore, importance is placed on the intuition behind the concepts to enable more profound understanding.
Students registering for this course would benefit from a solid grounding in mathematics, statistics or programming.
Teaching Format
The teaching activities consist of lectures and lessions.
The language of instruction is English.
Assessment
The course is examined through an on-campus written exam and assignments.
