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Linear algebra is the study of vector spaces and linear mappings between them. In this course, we will begin by reviewing topics you learned in Linear Algebra I, starting with linear equations, followed by a review of vectors and matrices in the context of linear equations. The review will refresh your knowledge of the fundamentals of vectors and of matrix theory, how to perform operations on matrices, and how to solve systems of equations. After the review, you should be able to understand complex numbers from algebraic and geometric viewpoints to the fundamental theorem of algebra. Next, we will focus on eigenvalues and eigenvectors. Today, these have applications in such diverse fields as computer science (Google's PageRank algorithm), physics (quantum mechanics, vibration analysis, etc.), economics (equilibrium states of Markov models), and more. We will end with the spectral theorem, which provides a decomposition of the vector space on which operators act, and singular-value decomposition, w… Details:
http://www.saylor.org/courses/ma212/
Categories:
Mathematics
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