Advanced Matrix Theory and Linear Algebra for Engineers

The course is taught by Prof. Vittal Rao, Centre for Electronics Design and Technology, IISc Bangalore.

In this course, you will learn Introduction to systems of linear equations, Vector spaces, Solutions of linear systems, Important subspaces associated with a matrix, Orthogonality, Eigenvalues and eigenvectors, Diagonalizable matrices, Hermitian and symmetric matrices, General matrices.

Epigenetics.
Prologue Part 2.
Prologue Part 3.
Linear Systems Part 1.
Linear Systems Part 2.
Linear Systems Part 3.
Linear Systems Part 4.
Vector Spaces Part 1.
Vector Spaces Part 2.
Linear Independence and Subspaces Part 1.
Linear Independence and Subspaces Part 2.
Linear Independence and Subspaces Part 3.
Linear Independence and Subspaces Part 4.
Basis Part 1.
Basis Part 2.
Basis Part 3.
Linear Transformations Part 1.
Linear Transformations Part 2.
Linear Transformations Part 3.
Linear Transformations Part 4.
Linear Transformations Part 5.
Inner Product and Orthogonality Part 1.
Inner Product and Orthogonality Part 2.
Inner Product and Orthogonality Part 3.
Inner Product and Orthogonality Part 4.
Inner Product and Orthogonality Part 5.
Inner Product and Orthogonality Part 6.
Diagonalization Part 1.
Diagonalization Part 2.
Diagonalization Part 3.
Diagonalization Part 4.
Hermitian and Symmetric matrices Part 1.
Hermitian and Symmetric matrices Part 2.
Hermitian and Symmetric matrices Part 3.
Hermitian and Symmetric matrices Part 4.
Singular Value Decomposition (SVD) Part 1.
Singular Value Decomposition (SVD) Part 2.
Back To Linear Systems Part 1.
Back To Linear Systems.
Epilogue.