Lecturer: Sebastian Stroppel
Language: in English
Time and place
Do, 10-12h, PC-Pool Raum -100, Hermann-Herder-Str. 10
Cannot be credited together with Prorgramming Exercises in Stochastics in Python.
Requirements on examinations, assessments and coursework will be described in the supplements of the module handbooks to be published as part of the course cataloque by end of October.
Content
This course is designed for students without prior knowledge in programming, but students who have already taken a first programming course might benefit as well . We will start with basic syntax and the standard library of python, including data types, functions, loops, regular expressions, and interacting with the operating system. For data analysis we learn dataframes using packages such as pandas (and relatives), see how we can interact with freely available APIs, make plots using matplotlob, and use numpy and scipy for standard procedures including numerical computations.
Within this course, you will pick a programming task of your interest, and implement your ideas based on your gained knowledge.