Analysis and application of numerical methods and algorithms to problems in the applied sciences and engineering. Applied linear algebra, including eigenvalue problems. Emphasis on use of conceptual methods in engineering, mathematics, and science. Extensive use of MATLAB package for programming and solution techniques. Prerequisite: either MATH 126 or Q SCI 293. Offered: AWSpS.
The course goals are to understand the basic concepts of linear algebra and to obtain an introduction to some aspects of computational techniques used in matrix methods. We will study basic concepts in linear algebra, including vectors, vector spaces, linear transformations, matrix-vector manipulations, solving linear systems, least squares problems, and eigenvalue problems. Matrix decompositions (e.g. LU, QR) will play a fundamental role throughout the course. The emphasis will be on practical aspects of linear algebra and numerical methods for solving these problems. Such problems arise constantly in science, engineering, finance, computer graphics.
Some familiarity with computer programming is assumed in this course, at the level of CSE 142 or AMATH 301. You are not expected to know MATLAB already. MATLAB programming will be taught as part of the course and the webpage has links to several online resources. You should also become adept at using the MATLAB language for numerical problem solving. MATLAB has many built-in functions for solving particular problems and you will learn how to use these. You should also gain an understanding of how they work, why they sometimes do not work, and how to use them intelligently.
MATH 308 (Linear Algebra) is not a prerequisite for this class. Both classes should complement one another and can be taken in either order.
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