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Use of the Python language for numerical methods, including solutions of systems of linear equations, solution of ordinary differential equations and systems of differential equations, boundary value problems, approximation techniques, area integration, statistics, random number generation, and Monte Carlo integration. Modelling projects and applications.
This course will teach students how to use Python to implement a wide range of numerical methods, including solutions to systems of linear equations, solutions of ordinary differential equations and system of differential equations, boundary value problems, approximation techniques, numerical integration, statistics, random number generation, Monte Carlo integration, and more. We will look at the theory and application of these numerical methods.By the end of the course you should be familiar with basic numerical methods, have a reasonable understanding of the mathematics behind these methods, and be able to implement these methods using Python. You should also be able to solve (engineering) problems using these methods and be able to interpret your results in the context of the original problems.
Both COSC121 and MATH103; or one of EMTH171, MATH170, orMATH171; or approval of the Dean of Engineering and Forestry. COSC121 can be replaced by COSC131, and MATH103 can be replaced by EMTH119 or MATH199.
EMTH271, MATH271
James Williams
Michael Langton
Domestic fee $847.00
International fee $4,988.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Mathematics and Statistics .