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News

• The oral exams will take place on G29-224.
• The data.npz file for the third assignment has been posted.
• The data file for the third assignment is online.
• The third assignment on interpolation and discrete Fourier transform (due 6/7/2018) is now online.
• The sign-up sheet for the oral exams is now available in the ISG admin office.
• The data for the second assignment is online.
• The second assignment is online. See below.
• Some students had trouble with lib.py with numpy 1.13. Here is a patched version.
• The first assignment is online; see below. It is due on 11.5.2018. Please email the course email address if you have questions.
• Tutorials will take place in G29-426.
• The first lecture will be on 3. April 2018.

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Lectures

Week 1: Introduction   Linear algebra recap Week 2: Floating point numbers (coming soon) Week 3/4: Linear systems Week 5: Least squares and LU decomposition Week 6: Eigen decomposition and diagonalization of matrices Week 6: Principal component analysis and singular value decomposition Week 7: Interpolation: Vandermonde matrix, Lagrange interpolation and splines Week 8: Quadrature Week 9 and 10: Discrete Fourier transform   Complex numbers Week 11: Solving the heat equation

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Tutorials

Week 1: Introduction to python and Numpy

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Assignments

Assignments 1: Programming   Skeleton code   Theory Assignments 2: Programming   Skeleton code   Data   Theory Assignments 3: Programming   Skeleton code   Data   data.npz   Theory

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Software

We will be working with python and the Numpy library in this course. On Linux you can install it using your package manager. On other operating systems it is convenient to use the Anaconda distribution which contains all necessary packages.

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Literature

There are plenty of books on the material covered in the course. Some that I found useful over the years are:

• G. Strang, Lineare Algebra. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003.
• G. Strang, Wissenschaftliches Rechnen. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010.
• G. H. Golub and C. F. Van Loan, Matrix Computations. The Johns Hopkins University Press, 1996.
• W. Dahmen and A. Reusken, Numerik für Ingenieure und Naturwissenschaftler, second ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008.
• T. Huckle and S. Schneider, Numerik für Informatiker. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002.

Please find the text that best matches your intuition and thinking.