Graduate Diploma in Mathematical Studies
University of Wollongong
About
The Graduate Diploma in Mathematical Studies is designed to consolidate and expand the mathematics or statistics knowledge gained in undergraduate studies, and to introduce candidates to mathematical or statistical research.
The Graduate Diploma in Mathematical Studies is only open to candidates who commence postgraduate courses in the School of Mathematics and Applied Statistics, who have completed the required subjects of the relevant postgraduate program and who do not wish to continue with that program.
Structure
The degree requires satisfactory completion of at least 48 credit points of subjects from postgraduate courses in the School of Mathematics and Applied Statistics, including MATH907 and no more than 12 credit points of List A (see the list below). The remaining credit points would normally be taken from the list of List B (see the list below) but may include up to 12 credit points of 900 level MATH/STAT/INFO subjects. In the case of someone transferring from the Master of Financial Mathematics, a maximum of 6cp may be for 900 level FIN subjects. The selection of subjects must be approved by the Academic Program Director, as appropriate.
Compulsory subject
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| MATH907 | Research Methods | 6 | Autumn |
List A - no more than 12 credit points from this list
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| MTH8201 | Multivariate and Vector Calculus | 6 | Autumn |
| MTH8202 | Differential Equations: Analysis and Aplication | 6 | Autumn |
| MTH8203 | Linear Algebra and Groups | 6 | Spring |
| MTH8212 | Mathematical Modelling | 6 | Spring |
| MTH8222 | Real Analysis | 6 | Autumn |
| MTH8206 | Random Variables and Estimation | 6 | Autumn |
| MTH8207 | Statistical Inference and Introduction to Model Building | 6 | Spring |
List B - at least 30 credit points from this list
| Subject Code | Subject Name | Credit Points | Session(s) |
|---|---|---|---|
| INFO812 | Mathematics for Cryptography | 6 | Autumn |
| INFO911 | Data Mining and Knowledge Discovery | 6 | Autumn |
| MATH805 | Partial Differential Equations (Enhanced) | 6 | Autumn |
| MATH812 | Advanced Applied Mathematical Modelling (Enhanced) | 6 | Spring |
| MATH813 | Case Studies in Applied Mathematics (Enhanced) | 6 | Not available in 2020 |
| MATH817 | Financial Mathematics (Enhanced) | 6 | Autumn |
| MATH818 | Optimisation and Applications (Enhanced) | 6 | Spring |
| MATH822 | Algebra (Enhanced) | 6 | Spring |
| MATH823 | Topology (Enhanced) | 6 | Spring |
| MATH824 | Calculus of Variations & Elementary Differential Geometry (Enhanced) | 6 | Not available in 2020 |
| MATH829 | Medical Mathematics (Enhanced) | 6 | Autumn |
| STAT804 | Stochastic Methods in Statistical Analysis (Enhanced) | 6 | Spring |
| STAT832 | Generalised Linear Models (Enhanced) | 6 | Autumn |
| STAT835 | Sample Surveys and Experimental Design (Enhanced) | 6 | Autumn |
Learning outcomes
Course Learning Outcomes (CLOs) are statements of learning achievement that are expressed in terms of what the learner is expected to know, understand and be able to do upon completion of a course. Students graduating from this course will be able to:
CLO Description 1 Review, analyse, consolidate and synthesise in-depth theoretical and technical knowledge in mathematics or statistics. 2 Develop cognitive and technical skills in either mathematics or statistics. 3 Independently analyse and generate solutions to complex problems. 4 Interpret and transmit complex mathematical or statistical knowledge, skills and ideas to others. 5 Apply complex knowledge and skills ethically to demonstrate sound judgement as a mathematician or statistician.
Institution
