Universität Wien

280448 VU Numerical methods (2022W)

8.00 ECTS (5.00 SWS), SPL 28 - Erdwissenschaften, Meteorologie - Geophysik und
Continuous assessment of course work
ON-SITE
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 90 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 03.10. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 04.10. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 05.10. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 05.10. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 10.10. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 12.10. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 12.10. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 17.10. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 19.10. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 19.10. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 24.10. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 25.10. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 31.10. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 07.11. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 08.11. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 09.11. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 09.11. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 14.11. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 16.11. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 16.11. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 21.11. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 22.11. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 23.11. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 23.11. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 28.11. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 29.11. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 30.11. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 30.11. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 05.12. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 06.12. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 07.12. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 07.12. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 12.12. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 13.12. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 14.12. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 14.12. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 09.01. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 10.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 11.01. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 11.01. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 16.01. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 17.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 18.01. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 18.01. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 23.01. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 24.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 25.01. 15:00 - 16:30 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Wednesday 25.01. 16:45 - 18:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 30.01. 11:30 - 13:00 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Tuesday 31.01. 09:45 - 11:15 Littrow-Hörsaal Astronomie Sternwarte, Türkenschanzstraße 17
  • Monday 06.02. 11:00 - 13:30 Hörsaal 4 ZfT Gymnasiumstraße 50 3.OG

Information

Aims, contents and method of the course

The aim of the course is to provide the student with the following tools/skills: statistical methods and tests, integration methods for common differential equations, regression and equalization calculus, approximation of functions, interpolation of functions, sampling of distributions, optimization, data visualization, introductory machine learning techniques, maximum likelihood and MCMC fitting techniques.
This will be achieved through lectures focused on the theory and exercises focused on the practical implementation of statistical tools and numerical methods. The programming language that will be used to present algorithms is python; students will receive an introductory tutorial to provide them with the necessary background to successfully carry out the computational tasks.

Assessment and permitted materials

Total grade: lectures 50% + exercises 50%

Lectures: Two mini-tests, currently planned on 14 November 2022 and 6 February 2023 and contributing respectively 20% and 30% to the final 50% grade from the lectures.

Exercises: weekly homework based on the lectures topics. The grade will depend on the evaluation of the submitted exercises and on the evaluation of the submitted report for a mini-project, each accounting for 25% of the final grade.

Minimum requirements and assessment criteria

In each of the two parts, lectures and exercises (including the mini-project) a minimum of 50% has to be achieved to count as passing. The submission of all exercise sheets and the mini-project is also required.

Examination topics

Based on the content of the lectures, for each of the two parts of the course (the first focused more on statistics and programming theory, the second on implementation of numerical methods). Homework, solved as part of the exercises, will aid and test students' understanding of the material covered in the lectures by applying statistical tools and numerical methods to real datasets.

Reading list

The lecture notes are provided as PDF files.

Selected chapters in the following literature are recommended:
- Statistics in Theory and Practice (Robert Lupton) [online version available at the library]
- Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data (Ivezić, Željko et al.) [only physical copies]
- Press, Teukolsky, Vetterling, Flannery: Numerical Recipes
- DeGroot and Schervish: Probability and Statistics
- Strang, G.: Introduction to Applied Mathematics

Association in the course directory

PM-NumMeth; PM-Num;

Last modified: Tu 31.01.2023 14:09