Python for Biologists - MB120C50

• Anglický název: Python for Biologists
• Český název: Python pro biology
• Zajišťuje: Katedra botaniky (31-120)
• Fakulta: Přírodovědecká fakulta
• Platnost: od 2023
• Semestr: zimní
• E-Kredity: 4
• Způsob provedení zkoušky: zimní s.:
• Rozsah, examinace: zimní s.:0/5, Z [DS]
• Počet míst: 15
• Minimální obsazenost: 5
• 4EU+: ne
• Virtuální mobilita / počet míst pro virtuální mobilitu: ne
• Stav předmětu: nevyučován
• Jazyk výuky: angličtina
• Poznámka: povolen pro zápis po webu
• Garant: Martha Kandziora, Dr. rer. nat.

Cíl předmětu

Poslední úprava: Mgr. Michal Štefánek (23.05.2022)

The main purpose of the course is to teach participants how to confidently interact with the command line and scripts written in python. Python can be used for solving common problems in biology, is easy to learn and offers a wide-variety of libraries for biologists. While programming for most people is developing software, simple and often repetitive tasks can be solved as well using small scripts. At the end of the course, the participants will be able to read and understand python code written by others, will be able to write small scripts themselves and have the competencies to adapt foreign code to own purposes.

As this is an introductory course into python, no requirements are needed - but familiarity with the command line is a plus. 

This course is taught in English as an intensive 5 days course. Offered in the winter semester only.

Požadavky ke zkoušce

Poslední úprava: Mgr. Michal Štefánek (20.04.2021)

Attending all classes; at the end of the course participants are asked to write a small script.

Sylabus

Poslední úprava: Mgr. Michal Štefánek (20.04.2021)

This intensive course will be a mix of theoretical and interactive practical parts, where students will use what they have just been learning.

Topics:

1) Introduction to bash - allowing to safely navigate when using clusters

2) Introduction to python - basics, graphical interfaces

3) Basic structure in python: strings, lists, sets, dataframes and related functionality

4) Control flow: if, else, while, for, etc

5) Best programming practice.

6) Data visualization with pandas and matplotlib