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 introduced to solve progressively more challenging problems.

Honours Pathway Option (HPO):

To do this option, students must have completed MATH2405 or STAT2001 or a mark of 60% or more in MATH2305 or MATH1116. The HPO expands on the theoretical aspects of the underlying algorithms, and uses alternative assessment to assess these theoretical aspects.

On satisfying the requirements of this course, students will have the knowledge and skills to:

1. Use high-level programming language such as Python 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

Assessment will be based on:

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

36 lectures and regular tutorials/computer labs.

Prerequisite course is MATH1116 or MATH2305 or MATH2405 or MATH2320 or STAT2001.

MATH2501