Vector spaces, linear maps, determinants, and eigenvalues and eigenvectors. Another standard is book’s audience: sophomores or juniors, usually with a background of at least one semester of calculus. This section contains free e-books and guides on Linear Algebra, some of the resources in this section can be viewed online and some of them can be downloaded. Topics covered includes: Matrices And Linear Equations, Vector Spaces, Linear Maps Between Vector Spaces, Spectral Theory Of Vector Spaces, The Geometry Of Inner Product Spaces, Adjoint Operators, Spectral Theory Of Inner Product.
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Course Description. This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices. Learn linear algebra for free—vectors, matrices, transformations, and more. Learn for free about math, art, computer programming, economics, physics, chemistry, biology, medicine, finance, history, and more. Khan Academy is a nonprofit with the mission of providing a free, world-class education for.
These windows in Philadelphia represent a beautiful block matrix. (Courtesy Gail Corbett. Used with permission.)
Instructor(s)
Prof. Gilbert Strang
MIT Course Number
18.06
As Taught In
Spring 2010
Level
Undergraduate
Translated Versions
Türkçe
Some Description | |
Instructor(s) | Prof. |
As Taught In | Spring 2002 |
Course Number | 2.24 |
Level | Undergraduate/Graduate |
Features | Lecture Notes, Student Work |
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Free Linear Algebra Software
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Course Description
Course Features
Course Highlights
This course parallels the combination of theory and applications in Professor Strang’s textbook Introduction to Linear Algebra. The course picks out four key applications in the book: Graphs and Networks; Systems of Differential Equations; Least Squares and Projections; and Fourier Series and the Fast Fourier Transform.
Course Description
This is a basic subject on matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, similarity, and positive definite matrices.
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