Lecture Videos of:
MATH 2940, Linear Algebra for Engineers
Videos are from Spring 2009 with Professor Andy Ruina.
List of Videos. Hosted on Cornell's Video On Demand service.
Videos by lecture:
01 - Introduction
02 - Matrices, Vectors, and Reduced Row Echelon Form
03 - Introduction to Rank and Matrix Algebra
04 - Example Problems and Review of Known Material
05 - Review of Transformations and Linear Transformations
06 - Vectors, Geometry, Transformations, and Transformation Matrices
07 - Linear Transformations Continued, Review of Matrix Multiplication, and Computer Graphing
08 - Inverse Matrices: Basic Facts and their Relationship with Linear Transformation
09 - Linear Transformation Review; the Kernel and Image
11 - Review of Kernel, Image, and Span; Intro to Subspace and Linear Independence
12 - Subspace, Redundancy, Linear Independence, and Bases
13 - Review and Introduction to Coordinates
14 - Change of Basis
15 - Review of Coordinate Transformations, Vectors, and Vector Spaces
16 - Vector Spaces and Isomorphisms
17 - Abstract Vectors Continued
18 - Abstract Vectors Continued and Change of Basis
19 - Matrices of Linear Transformations with Abstract Vectors
20 - An example of Vector Spaces and Orthogonality
22 - Gram-Schmidt and QR Factorization
23 - Review of Gram-Schmidt and Orthogonal Transformations
24 - Examples of Orthogonal Matrices
25 - Orthogonal Matrices and Examples
26 - Projections and Least Squares
27 - Curve Fitting and the Inner Product
28 - Inner Product Spaces and Function Approximation
32 - Introduction to Eigenvalues and Eigenvectors
33 - Finding Eigenvectors and Eigenvalues
34 - Eigenvectors and Eigenvalues continued
35 - Eigenvectors and Eigenvalues continued; Diagonalization
36 - Examples of Eigenvector and Eigenvalue Problems; Linear Transformations
37 - Complex Eigenvalues and Complex Number Review
38 - Diagonalization Review and Symmetric Matrices
39 - Symmetric Matrices, Eigenvectors and Eigenvalues, and Examples
40 - Springs
and Masses; Singular Value Decomposition (Part I)
41 - Singular
Value Decomposition (SVD) (Part II)