Course Structure
Week 1
Vectors, scalar/cross products, distances, lines, planes
Week 2
Linear maps, homogeneous coords, vector spaces
Week 3
Gauss elimination, kernel/image, Hamming codes
Week 4
QR decomposition, Gram-Schmidt, least squares
Week 5
Complex numbers, eigenvalues, Markov chains, PageRank
Learning Goals (Week 5)
-
1
Complex numbers: polar form, Euler's formula
-
2
Similar matrices and invariant properties
-
3
Eigenvalues and eigenvectors computation
-
4
Algebraic vs geometric multiplicity
-
5
Diagonalization of matrices
-
6
Markov processes and stochastic matrices
-
7
PageRank algorithm
Materials
27 Presentations
German + English
243 Figures
Python-generated
LaTeX Source
Beamer/Madrid
100+ Scripts
Matplotlib charts
Technical
LaTeX Beamer
Madrid theme, 8pt, 16:9
Python + Matplotlib
Vector PDF output
Purple/Lavender
Consistent color scheme