A rigorous mathematical introduction to linear algebra, directed at physics or engineering students, but also beneficial to neuroscientists and others who require linear and matrix algebra for research. Course assignments offer practice in working with linear maps between vector spaces, how these can be realized as matrices, and how this can be applied to solving systems of linear equations. Topics include matrix operations, solving systems of linear equations, eigenvalues, eigenvectors, diagonalization and Gram-Schmidt orthonormalization. Not intended for mathematicians.
Fields, vector spaces, and bases.
Matrix operations and solving systems of linear equations.
Row reduction and determinants.
Change of coordinates.
Eigenvalues, eigenvectors, diagonalisation.
Gram-Schmidt orthonormalisation.
Homework 50% – approx. 3 hours per week. There will be 10 homework sets, one each week.
Final exam 50%
Linear Algebra Done Wrong – Sergei Treil
Alternate years course, AY2025