Linear Algebra - Foundations to Frontiers

Learn the mathematics behind linear algebra and link it to matrix software development.

Course Description

Linear Algebra: Foundations to Frontiers (LAFF) is packed full of challenging, rewarding material that is essential for mathematicians, engineers, scientists, and anyone working with large datasets. Students appreciate our unique approach to teaching linear algebra because: It’s visual It connects hand calculations, mathematical abstractions, and computer programming It illustrates the development of mathematical theory It’s applicable In this course, you will learn all the standard topics that are taught in typical undergraduate linear algebra courses all over the world, but using our unique method, you'll also get more! LAFF was developed following the syllabus of an introductory linear algebra course at The University of Texas at Austin taught by Professor Robert van de Geijn, an expert on high performanc... Read More »

Linear Algebra: Foundations to Frontiers (LAFF) is packed full of challenging, rewarding material that is essential for mathematicians, engineers, scientists, and anyone working with large datasets.

Students appreciate our unique approach to teaching linear algebra because:

  • It’s visual
  • It connects hand calculations, mathematical abstractions, and computer programming
  • It illustrates the development of mathematical theory
  • It’s applicable

In this course, you will learn all the standard topics that are taught in typical undergraduate linear algebra courses all over the world, but using our unique method, you’ll also get more! LAFF was developed following the syllabus of an introductory linear algebra course at The University of Texas at Austin taught by Professor Robert van de Geijn, an expert on high performance linear algebra libraries. Through short videos, exercises, visualizations, and programming assignments, you will study Vector and Matrix Operations, Linear Transformations, Solving Systems of Equations, Vector Spaces, Linear Least-Squares, and Eigenvalues and Eigenvectors. In addition, you will get a glimpse of cutting edge research on the development of linear algebra libraries, which are used throughout computational science.

MATLAB licenses will be made available to the participants free of charge for the duration of the course.

We invite you to LAFF with us!

Read Less
Course Outcomes:
  • Connections between linear transformations, matrices, and systems of linear equations
  • Partitioned matrices and characteristics of special matrices
  • Algorithms for matrix computations and solving systems of equations
  • Vector spaces, subspaces, and characterizations of linear independence
  • Orthogonality, linear least-squares, eigenvalues and eigenvectors
Course Details:

Prerequisites

High School Algebra, Geometry, and Pre-Calculus.
About Instructor:

Maggie Myers - Lecturer, Department of Statistics and Data Sciences

Dr. Maggie Myers is a lecturer for the Department of Computer Science and Division of Statistics and Scientific Computing. She currently teaches undergraduate and graduate courses in Bayesian Statistics. Her research activities range from informal learning opportunities in mathematics education to formal derivation of linear algebra algorithms.

Earlier in her career she was a senior research scientist with the Charles A. Dana Center and consultant to the Southwest Educational Development Lab (SEDL). Her partnerships (in marriage and research) with Prof. van de Geijn have lasted for decades and seem to be surviving the development of this MOOC.


Robert van de Geijn - Professor of Computer Science

With a Ph.D. in applied mathematics, Robert van de Geijn is a professor of Computer Science and a member of the Institute for Computational Engineering and Sciences and the Division of Statistics and Scientific Computation at the University of Texas at Austin.

Prof. van de Geijn is a leading expert in the areas of high-performance computing, linear algebra libraries, parallel processing, and formal derivation of algorithms. He is the recipient of the 2007-2008 President’s Associates Teaching Excellence Award from The University of Texas at Austin.


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