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 a easy learnable programming language and thus ideal for beginners. Furthermore, over the last couple of years high-quality programming libraries tailored for scientific computing and data analysis have been developed.
Poster
Date and Location
The course is held twice in two consecutive weeks:
Date:
First school: Monday, June 8, 2015 - Thursday, June 11, 2015
Second school: Monday, June 15, 2015 - Thursday, June 18, 2015
Location: Y36-K-08 (UZH Campus Irchel)
Program
You can find the preliminary programme
here.
Application
Due to the limited computing resources for the course the number of participants is limited. If you are interested to participate in this course, please apply via the corresponding
form.
The closing date for applications is
March 31, 2015.
No participation fee has to be paid.
Prerequisites
To benefit optimally from the course it is useful to posses a basic knowledge of Python. We encourage everybody who has only limited knowledge to study the
introductionary material. It is also beneficial for all other people to refresh their knowledge by working through them.
Contact
For any further questions please write to
python@physik.uzh.ch
Lecturers
Sponsors
This course is supported by the
Physics Institute
and the
Faculty of Science
of the University of Zurich. Thank you!