Course description
Linear Algebra - Foundations to Frontiers
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.
Upcoming start dates
Who should attend?
Prerequisites
High School Algebra, Geometry, and Pre-Calculus.
Training content
- Week 0 Get ready, set, go!
- Week 1 Vectors in Linear Algebra
- Week 2 Linear Transformations and Matrices
- Week 3 Matrix-Vector Operations
- Week 4 From Matrix-Vector Multiplication to Matrix-Matrix Multiplication
- Exam 1
- Week 5 Matrix-Matrix Multiplication
- Week 6 Gaussian Elimination
- Week 7 More Gaussian Elimination and Matrix Inversion
- Week 8 More on Matrix Inversion
- Exam 2
- Week 9 Vector Spaces
- Week 10 Vector Spaces, Orthogonality, and Linear Least Squares
- Week 11 Orthogonal Projection and Low Rank Approximation
- Week 12 Eigenvalues and Eigenvectors
- Final
Course delivery details
This course is offered through The University of Texas at Austin, a partner institute of EdX.
6-10 hours per week
Costs
- Verified Track -$99
- Audit Track - Free
Certification / Credits
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
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edX
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