Stud.IP Uni Oldenburg
University of Oldenburg
29.11.2021 21:27:26
neu780 - Introduction to Data Analysis with Python (Complete module description)
Original version English Download as PDF
Module label Introduction to Data Analysis with Python
Module code neu780
Credit points 6.0 KP
Workload 180 h
2 SWS Lecture total workload 90h: 30h contact / 60h individual reading 2 SWS Supervised exercise total workload 90h: 45h contact / 45h solving programming exercises
Institute directory Department of Neurosciences
Applicability of the module
  • Master's Programme Biology (Master) > Skills Modules
  • Master's Programme Biology (Master) > Skills Modules
  • Master's Programme Neuroscience (Master) > Skills Modules
Responsible persons
Winklhofer, Michael (Module responsibility)
Winklhofer, Michael (Authorized examiners)
Skills to be acquired in this module

+ Neurosci. knowlg.
++ Maths/Stats/Progr.
+ Data present./disc.

The ojective of the module is the acquistion of programming skills with focus on analysis of neurobiological datasets, using the programming language python. Python is available for any computer platform (PC, Mac, Linux) and is open source (for free), see

Students will learn how to write effective scripts for data processing and visualisation, making use of pre-existing program libraries for various generic purposes (maths, statistics, plotting, image analysis).

Typical applications will be analysis of time series (e.g., electrophysiological recordings, movement data), images (e.g. immunohistochemical images, MRI slices), and spatio-temporal correlations in volume data.
Students will also learn how to produce synthetica data from various noise models to assess signal-to-noise ratio in instrumental datasets.
Module contents
Data types and data structures, control structures, functions, modules, file input/output Standard libraries and SciPy libraries (Matplotlib, NumPy,...), scikit-image, VPython, ...
Reader's advisory
Language of instruction English
Duration (semesters) 1 Semester
Module frequency semester break, annually
Module capacity 20
Reference text
Shared course components with (cannot be credited twice): pb328 "Einf├╝hrung in Datenanalyse mit Python" (Professionalisierungsmodul im Bachelorstudiengang Biologie)
Modullevel / module level
Modulart / typ of module Wahlpflicht / Elective
Lehr-/Lernform / Teaching/Learning method
Vorkenntnisse / Previous knowledge No prior knowledge in programming required, but useful.
Course type Comment SWS Frequency Workload of compulsory attendance
2 WiSe 28
2 WiSe 28
Total time of attendance for the module 56 h
Examination Time of examination Type of examination
Final exam of module
term break, immediately after the course (2 weeks in February)
assignment of programming exercises, 4 out of 5 exercises to be assessed