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Mathematical Sciences Institute · ANU College of Systems and Society
This course explores elements of scientific computing, focusing on methods for solving or approximating the solution of calculus and linear algebra problems associated with real-world applications. By drawing on non-trivial problems from disciplines including physics, engineering and chemistry, and sophisticated scientific computing and visualisation environments, students are introduced to the basic computational concepts of stability, accuracy and efficiency. New numerical methods and techniques are developed to solve progressively more challenging problems. Note: Graduate students attend joint classes with undergraduates but will be assessed separately. The assessment will have a greater focus on more theoretical aspects of the material.
10 workshop responses demonstrating the capacity to use relevant software
Learning outcomes 2, 3, 4, 5
5 written assignments demonstrating a rigorous, problem-based understanding of underlying algorithms and mathematical techniques
Learning outcomes 1, 2, 4, 5
Final examination
Learning outcomes 1, 2, 3, 4, 5
The expected workload will consist of approximately 130 hours throughout the semester including: - Face-to face component which may consist of 3 x 1 hour lectures per week (36 hours) as well as a total of 20 hours of workshop time. - Approximately 74 hours of self-study per semester which will include preparation for lectures and completion of assessment tasks.
This course has no prescribed texts.