PhD course: Advanced Scientific Programming with Python (3 hp)

This course is targeted towards PhD students from all disciplines who regularly use programming in their research. Our plan is to introduce commonly used software development tools and help you become better programmers. This course is going to be very practical with many hands-on examples, because in the end programming is mostly about practicing! 

Registering for the course

Please apply for the course here.

How to be prepared for the course

This course will not cover the very basics of Python programming. However, we have compiled a list of resources that might help you getting started: Preparation material.
In order to follow the content of this course, you should be familiar with and able to follow this simple code example: minimal.py.

Bring your own laptop

This course requires you to bring your own laptop, and you will need a couple of things installed and running before you come to the first lecture. You can find installation instructions on the next section.
If, for some reason, you are not able to bring a laptop, please contact us ahead of time so that we can figure out a solution for you.

Install Python

Please have a look at our installation guide.

Questions

If you have any questions about the course, don’t hesitate to contact us!
Filipe Maia (filipe.maia@icm.uu.se)

Course schedule

Day Time Topic Room
Monday, 2024-02-19 09.15-12.00 Basics:An introduction to the UNIX shell, interactive Python and git repositories Å2002
13.15-16.00 Hands-on exercises Å2002
Tuesday, 2024-02-20  09.15-12.00 Best practices I:Organizing, debugging and profiling of code Å2002
13.15-16.00 Hands-on exercises Å2002
Wednesday, 2024-02-21 09.15-12.00 High performance computing:Speed optimization using Numpy, Cython, MPI and GPU acceleration Å2002
13.15-16.00 Hands-on exercises and coding project Å2004
Thursday, 2024-02-22 09.15-12.00 Best practices II:Testing, documenting and packaging of code Å2002
13.15-16.00 Hands-on exercises and coding project Å2002
Friday, 2024-02-23 09.15-12.00 Data containers:Efficient memory storage using HDF5, Pytables and Pandas BMC A9:001
13.15-16.00 Hands-on exercises and coding project Å2002