neu780 - Biological Data Analysis with Python (Complete module description)

Module label	Biological 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 (authorised to take exams)
Prerequisites
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 https://www.python.org/. 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, ...
Recommended reading	open access http://www.swaroopch.com/notes/python/ http://docs.python.org/3/tutorial/index.html
Links
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 "Einführung in Datenanalyse mit Python" (Professionalisierungsmodul im Bachelorstudiengang Biologie)

Type of course	SWS	Frequency	Workload of compulsory attendance
Lecture	2	WiSe	28
Exercises	2	WiSe	28
Total module attendance time			56 h

Examination	Prüfungszeiten	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