MAST30028 Numerical Methods & Scientific Computing
|Dates & Locations:|| |
This subject has the following teaching availabilities in 2017:
Semester 2, Parkville - Taught on campus.Show/hide details
Timetable can be viewed here.
For information about these dates, click here.
|Time Commitment:||Contact Hours: 2 x one hour lectures and 1 x two hour computer laboratory class per week |
Total Time Commitment:
Estimated total time commitment of 170 hours
Study Period Commencement:
Semester 1, Semester 2
Plus one of:
Study Period Commencement:
Summer Term, Semester 1, Semester 2
Note - In 2018 it is planned to add in the following prerequisite:
Plus one of
|Recommended Background Knowledge:|| |
Some ability in computer programming is helpful
|Non Allowed Subjects:||None|
|Core Participation Requirements:|| |
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.
It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability
CoordinatorAssoc Prof Steven Carnie
|Subject Overview:|| |
Most mathematical problems arising from the physical sciences, engineering, life sciences and finance are sufficiently complicated to require computational methods for their solution. This subject introduces students to the process of numerical approximation and computer simulation, applied to simple and commonly encountered stochastic or deterministic models. An emphasis is on the development and implementation of algorithms for the solution of continuous problems including aspects of their efficiency, accuracy and stability. Topics covered will include simple stochastic simulation, direct methods for linear systems, data fitting of linear and nonlinear models, and time-stepping methods for initial value problems.
|Learning Outcomes:|| |
On completion of this subject, students should:
|Recommended Texts:|| |
C. Moler, Numerical Computing with Matlab, SIAM, 2004.
|Breadth Options:|| |
This subject potentially can be taken as a breadth subject component for the following courses:
You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
|Generic Skills:|| |
In addition to learning specific skills that will assist students in their future careers in science, they will have the opportunity to develop generic skills that will assist them in any future career path. These include:
This subject is available for science credit to students enrolled in the BSc (both pre-2008 and new degrees), BASc or a combined BSc course.
|Applied Mathematics |
Applied Mathematics (specialisation of Mathematics and Statistics major)
Science-credited subjects - new generation B-SCI and B-ENG.
Selective subjects for B-BMED