Mathematical Modelling and Computation
Mathematics prerequisites and Mathematics Learning Support
In 2024, some mathematics prerequisites for undergraduate students commencing in Semester 1 2025 were removed.
It has been identified that this curriculum component (Program, Major or Minor) has been affected. To ensure success, make sure you are aware of the required level of mathematics (assumed knowledge) for this curriculum component. Visit the mathematics learning support webpage, to understand your pathway to success, including the sequence of units you should complete and the support services available.
About the major
Mathematical modelling is becoming an important tool in science, engineering, economics, business and society in general, due to the rise of computer power and data availability. In this major you will learn the mathematical techniques that are essential for model development, application and assessment including computational and numerical skills. These techniques include ordinary and partial differential equations, which use ideas from calculus, and stochastic modelling, which uses ideas from probability theory.
In this major we use Python as the computational platform. This powerful software is rapidly becoming industry standard and will enable you to solve and manipulate models so that you get to grips with model outputs. You will have opportunities to apply mathematical modelling techniques in biology, medical sciences, physics and chemistry and engineering applications.
Graduate opportunities
When you complete this major you will have the mathematical modelling and computational foundations to build a career in research (Universities, CSIRO), the public sector (Bureau of Meteorology, state and federal government agencies), or the private sector (engineering, consulting, IT, finance).
Requirements for completion
The Mathematical Modelling and Computation major and minor requirements are listed in the Mathematical Modelling and Computation unit of study table.
Contact and further information
School of Mathematics and Statistics
University of Sydney NSW 2006
Learning outcomes
Students who graduate from Anatomy and Histology will be able to:
| No. | Learning outcome |
|---|---|
| 1 | Apply mathematical concept to analyse specific problems and identify the appropriate mathematics to realise a solution. |
| 2 | Recognise the connections between mathematics and other disciplines, and how mathematical ideas are embedded in other contexts. |
| 3 | Model a variety of systems efficiently using computer programming and statistical analysis skills. |
| 4 | Represent real-world systems from science and technology in a mathematical framework. |
| 5 | Analyse, solve and evaluate the performance of mathematical models using appropriate methods. |
| 6 | Demonstrate a capacity to pursue independent mathematical learning and deepen understanding of the behaviour of a given system, including identifying relevant disciplinary material and sources. |
| 7 | Demonstrate capacity to work both independently and collaboratively within mathematics and computation and beyond in a variety of contexts. |
