This course introduces important algorithms and techniques of scientific computing, focussing 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.

This is an HPC, taught at a level requiring greater conceptual understanding than MATH3511.

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.

UG Assessment will be based on:

• Five written assignments involving maths and programming problems (70%; LO 1, 2, 3, 4)
• Open-book examination (30%; LO 1, 2, 3, 4)

PG Assessment will be based on:

36 lectures and regular tutorials/computer Labs.

Prerequisite is: mark greater than 60 in MATH2305; or MATH2405; or MATH2320; or STAT2001; or MATH3116; or MATH3511

In addition to the formal pre-requisite requirements, it is recommended that students have undertaken a programming course such as COMP1100 or COMP1730.