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Lund University
Numerical Analysis: Advanced Course in Numerical Algorithms with Python/SciPy
<p>The course provides an algorithm-oriented complement to the more basic and special courses in numerical analysis that are focused on method analysis. Based on the student's previously acquired knowledge in numerical analysis, the course also intends to practice such skills that have special importance in professi…
- Higher education
- Information unavailable
- 31 August 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
<p>The course provides an algorithm-oriented complement to the more basic and special courses in numerical analysis that are focused on method analysis. Based on the student's previously acquired knowledge in numerical analysis, the course also intends to practice such skills that have special importance in professional life. In the course, the focus is on the view that a program is a tool developed in a longer process and in a group and which will later be used by others. The course emphasizes the connection between mathematical theory, complex computational algorithms and modern programming language.</p><p>The course treats:</p> <ul> <li>Object-oriented programming style for scientific computing. SciPy/NumPy data structures.</li> <li>Examples of complex numerical algorithms from different fields within numerical analysis.</li> <li>Coupling to numerical libraries in C and Fortran (Netlib).</li> <li>Automatic tests in scientific computing. The use of Python to control system processes.</li> </ul>
Admission scores
Entry requirements
90 higher education credits in mathematics and science, including knowledge equivalent to NUMA01 Computational Programming with Python, 7.5 credits, and an additional 7.5 credits in numerical analysis.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2026-08-31
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.lu.numn21.13072.20262
- Last checked
- 2026-09-23T10:38:33.477975+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.lu.numn21.13072.20262
- Offering identity in the source
- e.uoh.lu.numn21.13072.20262
- Education-form source code
- HS
- Education code in the source
- NUMN21
- Change time according to the source
- 2026-02-03T10:34:12
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.