This course was originally written by Thomas Robitaille, and was carefully adapted by Markus Demleitner and myself.
The web page for this course is [http://wwwstaff.ari.uni-heidelberg.de/rschmidt/pycourse/].
The lecturer is Robert Schmidt. You can contact me during the course and at rschmidt@uni-heidelberg.de
The block course lasts five days, and each day will follow this schedule:
The lectures will be mixed with exercise sessions - from time to time I will give you 5 or 10 minutes to complete a given task/exercise. There will be problem sets during the week, and you will be required to hand these in a deadline indicated on the problem sheet. An average of 60% [=54 points] in the problem sets will be required to obtain 2 credits points at the end of the course.
The course will be in English or German as convenient.
I am happy to review or talk about your code/solutions to exercises.
All solutions should be submitted as IPython (/Jupyter) notebooks or python programs (one notebook/program per problem set).
-> Please use a filename that contains the name of the problem sheet and your name.
-> Only submit the program (.py or .ipynb), do not submit data downloaded from the course web page.
Submissions have to be entered in the uebungen system.
The following criteria are taken into account for grading problem sets - the notebook/program should:
Please make use of the ability to add comments and text around your code. Make it so that someone not familiar with the problem could read it and understand your solution.
There is never a unique solution to a problem, so it does not matter if your programs do not look the same as somebody else's! What matters most is that you get a chance to make mistakes and learn from them.
Problem set submissions need to be handed in separately for each participant.
The deadlines for the Problem Sets are:
Problem Set 1 Thursday, October 10th 2024, 7pm CEST
Problem Set 2 Thursday, October 17th 2024, 7pm CEST
Problem Set 3 Thursday, October 24th 2024, 7pm CEST
The default is to use the jupyter server (see below), but if you would like to use Python on your laptop, you have several possibilities:
Please choose the 'thinclient' option. This opens a very basic client server that will run a browser for you. It is all you need for this course.
The default is to point the browser to the server https://jupyter.kip.uni-heidelberg.de for this course.
But there are also identical machines jupyter2 and jupyter3 to be used [e.g., in case of overcrowding].
Please login to one of these three machines.
You can download the notebooks I'm showing, the problem sets and the ancillary data files from the course web page here
The simplest way to upload the files to the jupyter server is the following:
The file should now be visible in the Home directory.
In the same directory you also find the 'data' directory. The contains material that will be used in this course. In case you used your account before, this may also be called 'data2'. You can ask me if you want to rename this.