- Lecture 1
Background in Linear Algebra. Basic definitions. Types and structures of quadratic matrices.
- Lecture 2
Vector and matrix norms. Range and kernel. Orthonormal vectors. Gram-Schmidt process. Eigenvalues and their multiplicities. Basic matrix factorizations and canonical forms: QR, diagonal form, Jordan form, Schur form. Basic matrix factorizations: SVD, LU, Cholessky.