Fachbereich 6 Mathematik/Informatik

Institut für Informatik

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Scientific programming in Python (co-taught by Christoph Stenkamp and Philipp Thölke)




In this course, we will handle the tools and methods you need for Scientific Programming in Python. We will deal with the python-libraries used to work with experiments and experimental data - from creating experiments, cleaning the data and working with the dataset to analyzing and plotting the results. This course is not taught by Kai-Uwe Kühnberger, but by Philipp Thölke and Christoph Stenkamp, students of Cognitive Science at the IKW.

As for our course schedule, we will first give a general introduction into git, python and pythonic programming as well as debugging, before we will delve into the SciPy-Stack. For that, we will look at numpy and pandas to deal with experiment data, matplotlib, plotnine, seaborn and jupyter widgets to visualize it, as well as expyriment and statsmodels, to give you an A to Z to create and analyze scientific experiments.

Note that we will not upload any lectures to the files-section of this course, but use GitHub to distribute the lecture material - the respective repository can be found at https://github.com/scientificprogrammingUOS/lectures and how to clone a repository is explained in part 2 of the introduction :)

Weitere Angaben

Ort: 35/E16
Zeiten: Di. 12:00 - 14:00 (wöchentlich), Do. 14:00 - 16:00 (wöchentlich) - Tutorial
Erster Termin: Di , 14.04.2020 12:00 - 14:00, Ort: 35/E16
Veranstaltungsart: Seminar (Offizielle Lehrveranstaltungen)


  • Cognitive Science > Bachelor-Programm
  • Cognitive Science > Master-Programm