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A continuation of 200-level linear algebra with computational and theoretical aspects and applications.
The course investigates and develops some of the fundamental concepts of matrix algebra, including matrix decompositions, positive definiteness, and solving linear systems. It also explores how matrix algebra can be used in a variety of applications, including problems in commerce, data science, engineering, operations research, and elsewhere.Topics Covered:Topics will be selected from the following list: Vector and matrix norms and condition numbers; QR-factorizations via Givens and Householder matrices; Singular Value Decompositions, Cholesky factorization; Fundamental spaces of a matrix; Least squares, and the use of QR-factorizations and the SVD to find the shortest solutions; Eigenvalues, eigenvectors, and their effcient calculation; Linear programming; Integer programming.
One of MATH203, EMTH211, orDATA203
MATH352, EMTH412
Students must attend one activity from each section.
Rachael Tappenden
Mingfeng Qiu
Fletcher, R; Practical methods of optimization ; 2nd ed.; Wiley, 1987.
Noble, Ben. , Daniel, James W; Applied linear algebra ; 3rd ed; Prentice-Hall, 1988.
Strang, Gilbert; Linear algebra and its applications ; 4th ed; Thomson, Brooks/Cole, 2006.
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Domestic fee $897.00
International fee $5,188.00
* 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 .