- Code MATH6103
- Unit Value 6 units
- Offered by Mathematical Sciences Institute
- ANU College ANU Joint Colleges of Science
- Course subject Mathematics
- Areas of interest Mathematics
- Academic career PGRD
- Dr Jordan Pitt
- Katie Glass
- Mode of delivery In Person
- Co-taught Course
Second Semester 2020
See Future Offerings
All activities that form part of this course will be delivered remotely in Sem 2 2020.
The use of mathematical models has grown rapidly in recent years, owing to the advent of cheap and powerful computers, expanding from applications in the physical and earth sciences to the biological and environmental sciences, and now into industry and commerce.
In this course we study:
- The process of starting with an initial succinct non-mathematical description of a problem
Formulate associated mathematical models.
- Introduce new mathematical techniques and then determine and interpret solutions that are useful in a real life context.
- General computational and mathematical techniques and strategies will be introduced by examining specific scientific and industrial problems.
The topics to be covered in this course include:
- Model type selection and formulation
- Data analysis techniques (time/space and frequency domain)
- State Space and Transfer Function Models
- Model Structure Identification
- Testing and Sensitivity Analysis
Computations will be done using modern high level scientific computing environments such as SCILAB or PYTHON.
Note: Graduate students attend joint classes with undergraduates but are assessed separately.
Upon successful completion, students will have the knowledge and skills to:
On satisfying the requirements of this course, students will have the knowledge and skills to:
1. Design a model based on the basic processes and behaviour of a system and different ways of representing them
2. Evaluate the issues in building and evaluating models, taking into account their purpose and prior knowledge
3. Explain and use some important modelling tools (transfer function, state space, frequency-domain and DE-based models as well as data analysis techniques)
4. Discuss the role of modelling in both industry and science
5. Explain sensitivity and uncertainty analysis techniques
Assessment will be based on:
- Exam (40%; LO 1, 2, 3, 4, 5)
- Project designing and evaluating a model for a selected system (30%; LO 1, 2)
- Three assignments demonstrating ability to apply techniques (10% each; LO 2, 3, 5)
In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle.
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WorkloadThree hours per week and regular workshops/computer labs.
Requisite and Incompatibility
You will need to contact the Mathematical Sciences Institute to request a permission code to enrol in this course.
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
- Domestic fee paying students
- International fee paying students
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|8586||27 Jul 2020||03 Aug 2020||31 Aug 2020||30 Oct 2020||In Person||View|