Stud.IP Uni Oldenburg
University of Oldenburg
03.08.2020 22:56:32
neu780 - Introduction to Data Analysis with Python (Complete module description)
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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
Faculty/Institute Department of Neurosciences
Used in course of study
  • Master's Programme Biology (Master) >
  • Master's Programme Biology (Master) >
  • Master's Programme Neuroscience (Master) >
Contact person
Module responsibility
Authorized examiners
Entry requirements
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 ---
Modulart Wahlpflicht / Elective
Lern-/Lehrform / Type of program
Vorkenntnisse / Previous knowledge No prior knowledge in programming required, but useful.
Course type Comment SWS Frequency Workload attendance
Lecture 2.00 WiSe 28 h
Exercises 2.00 WiSe 28 h
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