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Linear Algebra - Foundations to Frontiers
edX
Course
Intermediate
Free to Audit
Certificate

Linear Algebra - Foundations to Frontiers

The University of Texas at Austin

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

8 hrs/week15 weeksEnglish118,124 enrolled
Free to Audit

About this Course

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. To see what former learners have to say about the course, read reviews on coursetalk . We invite you to LAFF with us!

What You'll Learn

  • 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

Prerequisites

  • High School Algebra, Geometry, and Pre-Calculus.

Instructors

M

Maggie Myers

Lecturer, Department of Statistics and Data Sciences

R

Robert van de Geijn

Professor of Computer Science

Topics

Systems Of Equations
Abstractions
Operations
Linear Algebra
Eigenvalues And Eigenvectors
Algebra

Course Info

PlatformedX
LevelIntermediate
PacingUnknown
CertificateAvailable
PriceFree to Audit

Skills

أنظمة المعادلات
التجريدات
العمليات
الجبر الخطي
القيم الذاتية والمتجهات الذاتية
Algebra

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