Skip to main content
### Details

#####
Courses that offer this unit

Non-award/non-degree study If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student. Cross-institutional study If you are from another Australian tertiary institution you may be permitted to undertake cross-institutional study in one or more units of study at the University of Sydney.
To help you understand common terms that we use at the University, we offer an online glossary.
## Media

## Student links

Year - 2020

Computational mathematics fulfils two distinct purposes within Mathematics. On the one hand the computer is a mathematician's laboratory in which to model problems too hard for analytical treatment and to test existing theories; on the other hand, computational needs both require and inspire the development of new mathematics. Computational methods are an essential part of the tool box of any mathematician. This unit will introduce you to a suite of computational methods and highlight the fruitful interplay between analytical understanding and computational practice. In particular, you will learn both the theory and use of numerical methods to simulate partial differential equations, how numerical schemes determine the stability of your method and how to assure stability when simulating Hamiltonian systems, how to simulate stochastic differential equations, as well as modern approaches to distilling relevant information from data using machine learning. By doing this unit you will develop a broad knowledge of advanced methods and techniques in computational applied mathematics and know how to use these in practice. This will provide a strong foundation for research or further study.

Classes

lecture 3 hrs/week, computer lab/tutorial 1 hr/week

Assessment

3 x homework assignments (total 60%), final exam (40%)

Assumed knowledge

A thorough knowledge of vector calculus (e.g., MATH2X21) and of linear algebra (e.g., MATH2X22). Some familiarity with partial differential equations (e.g., MATH3X78) and mathematical computing (e.g., MATH3X76) would be useful.

Faculty: Science

Semester 1

24 Feb 2020

Department/School: Mathematics and Statistics Academic Operations

Study Mode: Normal (lecture/lab/tutorial) day

Census Date: 31 Mar 2020

Unit of study level: Honours

Credit points: 6.0

EFTSL: 0.125

Available for study abroad and exchange: Yes

Faculty/department permission required? No

Location

Camperdown

More details

HECS Band: 2

Leadership for good starts here

ABN: 15 211 513 464

CRICOS Number: 00026A

TEQSA: PRV12057