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.

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.

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

36 lectures and regular tutorials/computer Labs.

Second year Mathematics is required.

Students should have undertaken an undergraduate major in Mathematics. It is also recommended that students have undertaken an introductory  programming course.