MATH 102 Applied Linear Algebra
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This MATH 102 Applied Linear Algebra course focuses on vectors, matrices, and least squares, as well as the basic topics of linear algebra applications. The main goal of this course is to allow beginners with little or no familiarity with linear algebra to lay a good foundation in the basic ideas and understand. They were used in many applications, including data selection, machine learning, artificial intelligence, tomography, navigation, imaging, and more financial and automatic control systems. The necessary background for the reader is familiarity with basic mathematical symbols.
The above-stated course is quite wide and it comprises numerous topics, such as, vectors and matrices, solutions of linear equations, equations of lines and planes, determinants, matrix algebra, orthogonality and applications (Gram-Schmidt), eigenvalues ??and eigenvectors and applications, complex numbers and many more.
Take a look at the second course in Linear Algebra from a computational and geometric perspective. It encompasses: Elementary Hermitian matrix, Schur's theorem, normal matrix, and quadratic form; The generalized Moore-Penrose inverse problem and the least-squares problem; Vector and matrix norms; Eigenvalues ??and singular numbers; Canonical form; Determinant and multiple linear algebras.
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