894004 Programming with Python (advanced) (in Eng.)
- Art
- Vorlesung und Übung
- Semesterstunden
- 2
- Vortragende/r (Mitwirkende/r)
- Galicia Andres, Edgar , Braunsfeld, Benedict , Petrov, Drazen , De Ruiter, Anita
- Organisation
- Angeboten im Semester
- Wintersemester 2024/25
- Unterrichts-/ Lehrsprachen
- Englisch
- Lehrinhalt
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Nowadays, the ability to design and write computer programs is becoming an indispensable skill. Among different programming languages, Python has become popular and widely used in the field of biosciences, for its readability, object-oriented programming and many available libraries that extend its functionality. This course is aimed at master and PhD students (bachelor students will be taken as well in case of free places on the participant list) who want to advance their programming / Python knowledge. It is primarily oriented at further development practical programming skills including manipulation, analysis and plotting of data, various calculations and automatization of different tasks. A number of Python modules and packages (e.g. matplotlib, numpy, scipy, pandas) will be introduced and used throughout the course. In addition, several advanced programming concepts (e.g. recursions, classes) will be discussed.
Topics
•General programming ideas
oShort overview of the basic concepts (flow control, functions, string manipulation)
oMore advanced and complex algorithms
oRecursions
oClasses
•Data manipulation, analysis, plotting
oSpectroscopic data
oProtein sequences, structures
oSimulation data
oDifferent databases
•Python packages
oNumpy
oPandas
oScipy
oMatplotlib
- Inhaltliche Voraussetzungen (erwartete Kenntnisse)
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Successfully passed exam of the Programming with Python (basic) course or passing an entry test.
- Lehrziel
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Students will learn how to write scripts using Python, as well as how to use different Python modules, primarily aimed at data analysis and plotting.
•Gain further understanding of how to design and develop computer programs
•Write code that is able to parse, prepare, filter and manipulate different data sets.
•Perform different analyses, including statistical tests, curve fitting.
•Generate various plot and visualizations of scientific data (biological databases, spectroscopic measurements, protein sequences and structures, etc.).
Noch mehr Informationen zur Lehrveranstaltung, wie Termine oder Informationen zu Prüfungen, usw.
finden Sie auf der Lehrveranstaltungsseite in BOKUonline.