This unit of study provides an introduction to programming and numerical methods. Topics covered include computer arithmetic and computational errors, solution of nonlinear equations, systems of linear equations, numerical integration and differentiation, interpolation and approximation, initial value problems for ordinary differential equations. This course will cover basic concepts of numerical optimization and applications such as for instance numerical optimization in the rapidly evolving domain of machine learning.
Unit details and rules
Academic unit | Mathematics and Statistics Academic Operations |
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Credit points | 6 |
Prerequisites
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A mark of 65 or above in [(12 credit points of MATH2XXX) or (6 credit points of MATH2XXX and 6 credit points of STAT2XXX or DATA2X02)] |
Corequisites
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None |
Prohibitions
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MATH3076 or MATH4076 |
Assumed knowledge
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Strong skills in linear algebra and the theory and methods of ordinary and partial differential equations for example (MATH2961 and MATH2965) or (MATH2921 and MATH2922) |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | Eduardo Goldani Altmann, eduardo.altmann@sydney.edu.au |
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Lecturer(s) | Eduardo Goldani Altmann, eduardo.altmann@sydney.edu.au |
Tutor(s) | Ayesha Sohail, ayesha.sohail@sydney.edu.au |