| Semester 2, 2022 Online | |
| Units : | 1 |
| Faculty or Section : | Faculty of Health, Engineering and Sciences |
| School or Department : | School of Mathematics, Physics & Computing |
| Grading basis : | Graded |
| Course fee schedule : | /current-students/administration/fees/fee-schedules |
Staffing
Examiner:
Overview
This course provides flexibility in honours and postgraduate programs to cater for the widely varying interests and chosen specialisations of students. Mathematicians need to be proficient in a wide range of mathematical concepts and techniques. Many of these are either only touched on or omitted from undergraduate programs. An opportunity to broaden the students' knowledge-base with more advanced concepts and techniques is provided in this course.
This course provides the opportunity for a student to pursue an area of study that will complement the other studies in the student's program. Typically, the course will consist of specialised investigations extending knowledge and skills in one of the areas listed in the Topics section below, or another Topic where appropriate and where a supervisor is available.
Course learning outcomes
On successful completion of this course students will be able to:
- demonstrate advanced knowledge and skills in the complementary study area.
Topics
| Description | Weighting(%) | |
|---|---|---|
| 1. |
Students should nominate the topic they wish to study; and then email the Course Examiner to enquire whether the topic and a suitable supervisor will be available in their semester of study, and for formal approval to enrol. One of the following topics can be chosen. The content of the course may vary from student to student. The weighting of the sub-topics within this course depends on the topic chosen and will be discussed with the supervisor. Algebra and Calculus: (prerequisite MAT1102 or ENM1600 or equivalent) This course covers and extends on topics of Algebra and Calculus II (MAT2100) such as ordinary differential equations, Fourier series, multivariable calculus, eigenvalues, line integrals (note this course is not compatible with MAT2100 or ENM2600). Modelling of Physical Systems: (prerequisite MAT2100 or MAT2500 or ENM2600 or equivalent) This course introduces extends upon concepts introduced in Mathematical Modelling and Dynamical Systems MAT3103. Topics may include 精东传媒app of Particular Dynamical Systems in Application to Engineering or other fields; Calculus of Variations. Qualitative Methods of Solutions of Differential Equations; 精东传媒app of Phase Plane Analysis; Exact Methods in Nonlinear Wave Theory. (This is not compatible with MAT3103) Financial Mathematics: (prerequisite STA2300 and MAT2100 (or MAT2500 or ENM2600) or equivalent) This course introduces and extends upon the methods and theory introduced in MAT3104 Mathematical Modelling in Financial Economics. Topics include financial and commercial applications of mathematics where Stochastic Differential Equations (SDEs) are of fundamental importance. SDEs also apply in many other areas in science and engineering and have many features that distinguish them from other mathematical models. (This is not compatible with MAT3104). Mathematics Education: This course is designed for students interested in expanding their knowledge in one or more areas of mathematics education. Topics could include: the role of language in learning and understanding mathematics; issues in adult, academic and everyday numeracy; fundamental constructs in mathematics education; history and philosophy of mathematics. Predictive Modelling with Random Forest, Multiple Regressions and Optimisation of Neural Networks: A number of analytical techniques related to ANN, MLR and RF models are introduced; and the data analyses and modelling is performed. The modelling in the course will focus on optimisation of an ANN and evaluation of the optimised model with MLR and RF models. RF models will be optimised by deducing the optimal combination of training algorithm, hidden transfer/output equations and data division between training, validation and testing subsets. Some programming in MATLAB, R or Python is assumed. Operations Research: (prerequisite MAT1102 or ENM1600 or equivalent) This topic introduces and extends upon the methods and theory in Operations Research 1 MAT2200. It focuses on the model development, analytical techniques and the background mathematics necessary for the solution and post-optimal analysis of linear programming, integer programming, transportation, assignment, graph, network, and critical path problems. (This is not compatible with MAT2200.) |
100.00 |
Text and materials required to be purchased or accessed
Student workload expectations
To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.
Assessment details
| Description | Group Assessment |
Weighting (%) | Course learning outcomes |
|---|---|---|---|
| Problem Solving | No | 50 | 1 |
| Report | No | 50 | 1 |