Advanced Matrix Theory and Linear Algebra for Engineers


Lecture 1 - Prologue - Part 1


Lecture 2 - Prologue - Part 2


Lecture 3 - Prologue - Part 3


Lecture 4 - Linear Systems - Part 1


Lecture 5 - Linear Systems - Part 2


Lecture 6 - Linear Systems - Part 3


Lecture 7 - Linear Systems - Part 4


Lecture 8 - Vector Spaces - Part 1


Lecture 9 - Vector Spaces - Part 2


Lecture 10 - Linear Independence and Subspaces - Part 1


Lecture 11 - Linear Independence and Subspaces - Part 2


Lecture 12 - Linear Independence and Subspaces - Part 3


Lecture 13 - Linear Independence and Subspaces - Part 4


Lecture 14 - Basis - Part 1


Lecture 15 - Basis - Part 2


Lecture 16 - Basis - Part 3


Lecture 17 - Linear Transformations - Part 1


Lecture 18 - Linear Transformations - Part 2


Lecture 19 - Linear Transformations - Part 3


Lecture 20 - Linear Transformations - Part 4


Lecture 21 - Linear Transformations - Part 5


Lecture 22 - Inner Product and Orthogonality - Part 1


Lecture 23 - Inner Product and Orthogonality - Part 2


Lecture 24 - Inner Product and Orthogonality - Part 3


Lecture 25 - Inner Product and Orthogonality - Part 4


Lecture 26 - Inner Product and Orthogonality - Part 5


Lecture 27 - Inner Product and Orthogonality - Part 6


Lecture 28 - Diagonalization - Part 1


Lecture 29 - Diagonalization - Part 2


Lecture 30 - Diagonalization - Part 3


Lecture 31 - Diagonalization - Part 4


Lecture 32 - Hermitian and Symmetric matrices - Part 1


Lecture 33 - Hermitian and Symmetric matrices - Part 2


Lecture 34 - Hermitian and Symmetric matrices - Part 3


Lecture 35 - Hermitian and Symmetric matrices - Part 4


Lecture 36 - Singular Value Decomposition (SVD) - Part 1


Lecture 37 - Singular Value Decomposition (SVD) - Part 2


Lecture 38 - Back To Linear Systems - Part 1


Lecture 39 - Back To Linear Systems - Part 2


Lecture 40 - Epilogue