This course presents the basic elements of scientific computing, in particular the methods for solving or approximating the solution of calculus and linear algebra problems associated with real world problems. Using a non-trivial model problem such as the heat equation, and sophisticated scientific computing and visualisation environments, students are introduced to the basic computational concepts of stability, accuracy and efficiency, as new numerical methods and techniques are introduce to solve progressively more challenging problems.

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 vector-based mathematical software such as MatLab/SciLab with proficiency and confidence
2. Use appropriate tools to verify the output and reliability of code/data
3. Use computing and visualisation software appropriately in scientific or engineering problems
4. Demonstrate a capacity for rigorous analysis in sophisticated scientific computing and visualisation environments

Assessment will be based on:

• 10 tutorial responses demonstrating a highly analytical capacity to use relevant software (30%; LO 1, 2, 3, 4)
• 5 written assignments demonstrating a rigorous, problem-based understanding of algorithms (30%; LO 1, 2, 3, 4)
• Final examination (40%; LO, 1, 2, 3, 4)