Applications of Linear Algebra Professional Certificate

What you will learn:

  • Model and solve real-world problems using Markov chains, determinants, dynamical systems, and Google Page Rank.
  • Construct the singular value decomposition (SVD) of a matrix and apply the SVD to estimate the rank and condition number of a matrix, construct a basis for the four fundamental spaces of a matrix, and construct a spectral decomposition of a matrix.
  • Apply the iterative Gram Schmidt Process and the QR decomposition to construct an orthogonal basis of a subspace.
  • Apply least-squares and multiple regression to construct a linear model from a data set.
  • Apply eigenvalues and eigenvectors to solve optimization problems that are subject to distance and orthogonality constraints.
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Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD (edX) EdX
Georgia Institute of Technology,GTx

Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD (edX)

Dive into the complex world of Linear Algebra with this comprehensive course. Learn about Orthogonality & Symmetric Matrices and the Singular Value Decomposition (SVD) – essential topics that underpin many areas of mathematics, computer science, and engineering. This course is ideal for those looking to enhance their understanding of advanced linear algebra concepts.

Self Paced
Self-Paced
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