Course overview
This course introduces students to decision-making and scenario-based analysis using stochastic modelling, including advanced topics in simulation.
Course learning outcomes
- Communicate how randomness and controlled variation can be used to model complex systems in a range of application domains such as industry, health, and transportation
- Create a model of a real-world problem specified in words and implement it as a discrete-event simulation
- Validate results from a discrete-event simulation
- Explore scenarios using simulation to elicit and compare possibilities
- Design simulation-based workflows to support decision-making in real-world contexts and explain the process
Degree list
The following degrees include this course