Advanced Linear Algebra for Computation

(CS 383C)

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Linear algebra is one of the fundamental tools for computational and data scientists. In Advanced Linear Algebra for Computing, you build your knowledge, understanding, and skills in linear algebra, practical algorithms for matrix computations, and analyzing the effects on correctness of floating-point arithmetic as performed by computers.

What You Will Learn

  • Deciphering a matrix using the Singular Value Decomposition
  • Quantifying and qualifying numerical error
  • Solving linear systems and linear least-squares problems
  • Computing and employing eigenvalues and eigenvectors

Syllabus

  • Norms (1 week)
  • The Singular Value Decomposition (1 week)
  • The QR Decomposition (1 week)
  • Linear Last Squares (1 week)
  • LU Factorization (1 week)
  • Numerical Stability (1 week)
  • Solving Sparse Linear Systems Part 1 (1 week)
  • Solving Sparse Linear Systems Part 2 (1 week)
  • Eigenvalues and eigenvectors (1 week)
  • Practical Solutions of the Hermitian Eigenvalue Problem (1 week)
  • The QR Algorithm Symmetric (1 week)
  • High Performing Algorithms (1 week)

Estimated Effort

9-12 hours per week

Course Category

Applications Course

Course Availability

  • Spring 2020
  • Fall 2020

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