• linear algebra:
  • vector space, basis and dimension;
  • linear map, matrix and rank;
  • Gauss-elimination and linear systems of equations;
  • determinants, eigenvalues and eigenvectors;
  • euclidean vector spaces and orthonormalization;
  • principal component transformation;
  • Applications of linear algebra in affine geometry, statistics, and coding theory  (linear codes)

• Klaus Jänich: Lineare Algebra, Springer-Lehrbuch, 10. Auflage 2004
• Dirk Hachenberger: Mathematik für Informatiker, Pearson 2005
• G. Grimmett, D. Welsh: Probability - An Introduction, Oxford Science Publications 1986
• Kurt Meyberg, Peter Vachenauer: Höhere Mathematik 1, Springer-Verlag, 6. Auflage 2001
• G. Berendt: Mathematik für Informatiker, Spektrum Akademischer Verlag 1994
• Oliver Pretzel: Error-Correcting Codes and Finite Fields, Oxford Univ. Press 1996

The sign-up for the tutorial sessions will be announced in due time.