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Third-Cycle Courses

Faculty of Engineering | Lund University

Details for Course FMNN25F Advanced Course in Numerical Algorithms with Python/SciPy

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General
  • FMNN25F
  • Temporary
Course Name
  • Advanced Course in Numerical Algorithms with Python/SciPy
Course Extent
  • 7.5
Type of Instruction
  • Course given jointly for second and third cycle
  • FMNN25, NUMN25
Administrative Information
  • 7154 (Centre of Mathematical Sciences / Numerical Analysis)
  • FMNN25, NUMN25
  •  -01-14
  • FN1/Anders Gustafsson

Current Established Course Syllabus

General
Aim
  • 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.
Contents
  • 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
Literature
  • 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

All Established Course Syllabi

1 course syllabus.

Valid from First hand in Second hand in Established
Autumn 2014 2014‑12‑16 17:25:06 2014‑12‑18 15:50:15 2015‑01‑14

Current or Upcoming Published Course Occasion

No matching course occasion was found.

All Published Course Occasions

No matching course occasions were found.

0 course occasions.

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