Week 1: Gaussian elimination, vectors, vector spaces and linear maps, matrices. Meckes Chapter 1.2, 1.3, 1.5, 2.1.
Week 2: Eigenvalues and eigenvectors, more on matrices, composition and matrix multiplication, transpose, isomorphisms, range, kernel. Meckes Chapter 2.1, 2.2, 2.3, 2.5.
Week 3. More on range, kernel. Eigenspaces and direct sumss. Linear independence, span, bases, change of bases. Similarity and diagonalizability. Meckes Chapter 2.5, 3.1, 3.2, 3.6.
Week 4: Exam 1.
Week 5: Inner products, orthonormal bases, subspaces and projection. Meckes Chapter 4.1-4.3.
Week 6: Norms, isometries. Intro to Singular Value Decomposition. Meckes Chapter 4.4, 4.5, 5.1.
Week 7: Singular Value Decomposition & applications. Meckes Chapter 5.2.
Week 8: Computing SVD and the Spectral theorem. Meckes Chapter 5.3, 5.4.