Please note that MATH6119 is run in semester 2 of even years i.e. 2014, 2016, 2018 etc.
This course introduces important algorithms and techniques of scientific computing, focusing on the area of numerical optimisation. The course will present both theoretical and practical aspects of the algorithms. The course is highly relevant to students from disciplines such as science, engineering or economics where skills in numerical computations are important.
Note: Graduate students attend joint classes with undergraduates but will be assessed separately.
Learning Outcomes
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. Use sophisticated scientific computing and visualization environments to solve application problems involving matrix computation algorithms.
2. Analyze numerical algorithms, and understand the relationships between the computational effort and the accuracy of these algorithms.
3. Interpret the results produced by computer implementations of numerical algorithms.
4. Explain the effects of errors in computation and how such errors affect solutions.
5. Demonstrate the necessary analytical background for further studies leading to research in applied mathematics or related disciplines.
Indicative Assessment
Assessment will be based on:
- Five written assignments involving maths and programming problems (50%; LO 1, 2, 3, 4)
- Open-book examination (30%; LO 1, 2, 3, 4)
- Computational case study project (20%; LO 1, 2 , 3, 4)
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
Three lectures 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.
Assumed Knowledge
Students should have undertaken an undergraduate major in Mathematics. It is also recommended that students have undertaken an introductory programming course.Fees
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:
- 2
- 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.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2019 | $4320 |
- International fee paying students
| Year | Fee |
|---|---|
| 2019 | $5700 |
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.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 9217 | 27 Jul 2020 | 03 Aug 2020 | 31 Aug 2020 | 30 Oct 2020 | In Person | N/A |
