Faculty of Information Technology
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
This unit provides an overview of computational science and an introduction to its central methods. It covers the role of computational tools and methods in 21st century science, emphasising modelling and simulation. It introduces a variety of models, providing contrasting studies on: continuous versus discrete models; analytical versus numerical models; deterministic versus stochastic models; and static versus dynamic models. Other topics include: Monte-Carlo methods; epistemology of simulations; visualisation; high-dimensional data analysis; optimisation; limitations of numerical methods; high-performance computing and data-intensive research.
A general overview is provided for each main topic, followed by a detailed technical exploration of one or a few methods selected from the area. These are applied in tutorials and laboratories which also acquaint students with standard scientific computing software (e.g., Mathematica, Matlab, Maple, Sage). Applications are drawn from disciplines including Physics, Biology, Bioinformatics, Chemistry, Social Science.
At the completion of this unit, students should be able to:
Examination (3 hours): 70%, In-semester assessment: 30%
Minimum total expected workload equals 12 hours per week comprising:
(a.) Contact hours for on-campus students:
(b.) Additional requirements (all students):
See also Unit timetable information
Dr Arun Konagurthu