Scientific Programming with Python June 23 - 27, 2025 UZH Campus Irchel |
How can I efficiently test if my code does what it should do? How can I improve
the performance of my code? What are ways to improve the development of code in
a collaborative environment? How can I handle my data in an easy way? Is it
possible to run existing C++ code in Python? If you come across these or similar
questions in your daily work as a scientist, you will very likely profit from
this course.
A large part of everyday's work of many scientists today is spent on
programming, debugging and maintaining software. Although there are tools and
procedures to do this in an efficient way, many scientists have never
experienced a thorough instruction in these techniques. Writing code is for
them only an auxiliary field in their work. Therefore they spend a significant
time on writing deficient code and reinventing the wheel. But ultimately
scientists should do science and not spend most of their time with software
engineering tasks...
This course will teach a selection of important programming techniques and
incorporates theoretical lectures followed by practical exercises where the
discussed techniques can be applied and tried out.
We use Python as programming language through the entire course. Python is
easy to learn and popular among scientists.
Over the last couple of years high-quality programming libraries tailored for
scientific computing and data analysis have been developed.
Nicola Chiapolini | 10-G-27 (044 63) 54026 / nicola.chiapolini@mnf.uzh.ch |
Christian Elsasser | che@physik.uzh.ch |
Jonas Eschle | jeschl@physik.uzh.ch |
Roman Gredig | rgredig@physik.uzh.ch |
Federica Lionetto | flionett@physik.uzh.ch |