Scientific Programming in Python

Welcome

This course page contains a summary of our course contents for your reference. It does not go in-depth on any particular topic - please refer to additional course materials for more information.

The contents of this page are under development. New pages will be added throughout the semester:

• Introduction (October 18 and 25, 2022)
• Data types and statements (October 25 and November 08, 2022)
• Functions and conditional execution (November 15 and 22, 2022)
• Advanced data types: lists, tuples, sets, dictionaries (November 22 and 29, 2022)
• Modules, file I/O (input/output) (December 06, 2022)
• Finishing the basics: more on functions, loops, dictionaries, and files (December 13, 2022)
• For efficiency’s sake: structured programs, packages, regular expressions (December 20, 2022 / January 10, 2023)
• Classes (January 17, 2023)
• Recursion and trees (January 24, 2023)
• Applications (Part I): Processing corpus data using NLTK, numpy, and matplotlib (January 31, 2023)
• Applications (Part II): Programming in experimental research (February 07, 2023)

Contents are based on course materials by Johannes Dellert (University of Tübingen). Additional resources – open access for further reading on any topic we are covering (!) – are:

• Sweigart, A. (2015). Automate the boring stuff with python: practical programming for total beginners. San Francisco, No Starch Press. (https://automatetheboringstuff.com/)

• Wentworth, P., Elkner, J., Downey, A.B., and Meyers, C. (2012). How to Think Like a Computer Scientist: Learning with Python 3 (RLE). (http://openbookproject.net/thinkcs/python/english3e/index.html)