Lineaire Algebra 2

This is the second half of the course covering fundamental aspects of Linear Algebra in BSc applied mathematics program (first year). Specifically, this course deals with the following topics:

+ Spectral analysis: eigenvectors and generalized eigenvectors of linear operators, eigenvalue decomposition (diagonalization) and the Jordan canonical form of a linear operator.

+ Orthogonalization: Inner products, adjoints, orthogonal projections, orthogonal bases and their properties, Gram-Schmidt procedure.

+ Optimization: least squares, quadratic forms and constrained quadratic optimization.

+ Singular value decomposition, low-rank approximations, pseudo inverses.

+ Computational aspects of the above concepts.

The topics covered are important for many fields in applied mathematics, including differential equations, data science, and numerical analysis.

The final grade of this course is determined by two tests; one in week 3.5 and one in week 3.9 or week 3.10.

After the final test, the final grade for this course is calculated as follows:

(grade test 1)/3 + 2*(grade test 2)/3

The course is passed if this grade is 5.75 or higher AND the grade of the second test is 5 or higher.

There will be one overall resit opportunity somewhere in Q4, which counts towards 100% of the final grade. It is not possible to do a resit for separate tests.

If the grade for the resit is higher than the final grade, it will replace the final grade.