Third-Cycle Courses

Faculty of Engineering | Lund University

Details for the Course Syllabus for Course FMNN25F valid from Autumn 2014

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  • To give doctoral students with experience of other programming languages training in implementing advanced numeric algorithms in Python/Scipy, in order to use this in other courses, in research or in industry.
  • Introduction to Python for students already familar with another programming language. The use of object oriented programming in scientific computing, Scipy/Numpy datastructures.

    Examples of complex numerical algorithms from varying subjects in numerical analysis,

    Linking to advanced numerical libraries in C and Fortran (Netlib).

    Automatic tests in scientific computing. Graphical representation of mathematical results (animation). The use of Python to control system processes.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • have developed an understanding for the basic principles of computational algorithms.

    have improved her/his knowledge about a number of important computational problems, and ways to attack them.
Competences and Skills
  • For a passing grade the doctoral student must
  • have developed a programming ability (for computational purposes) at a high level.

    have learnt how to code, test and evaluate the results of complex numerical algorithms, using established programme libraries.

    be able to carry out a group programming project, including identifying subproblems, distribution of tasks within the group and responsibility for the completion of his/her task.

    be able to account for a computational project, both in a written report and orally.
Judgement and Approach
  • For a passing grade the doctoral student must
Types of Instruction
  • Lectures
  • Exercises
Examination Formats
  • Written assignments
  • Miscellaneous
  • A larger programming project to be carried out in group, with a written report to be presented at a seminar. Opposition on the report of another group.
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
  • Basic course in numerical analysis. Programming experience in some of the languages Java, C, C++, Fortran, Python and Matlab.
Selection Criteria
  • Führer, C., Solem, J. & Verdier, O.: Computing with Python: An Introduction to Python for Science and Engineering. Pearson, 2013. ISBN 9780273786436.
Further Information
Course code
  • FMNN25F
Administrative Information
  •  -01-14
  • FN1/Anders Gustafsson

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