a Summer School by the G-Node and the University of Camerino
Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game.
We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist.
This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and of a version control system such as git, subversion, mercurial, or bazaar is assumed. Participants without any prior experience with Python and/or git should work through the proposed introductory material before the course.
We are striving hard to get a pool of students which is international and gender-balanced.
2–7 September, 2019. Camerino, Italy.
You can apply online: https://python.g-node.org/wiki/applications
Application deadline: 23:59 UTC, 26 May, 2019.
There will be no deadline extension, so be sure to apply on time. Be sure to read the FAQ before applying: https://python.g-node.org/wiki/faq
Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves.
• Version control with git and how to contribute to open source projects with GitHub • Tidy data analysis and visualization • Testing and debugging scientific code • Advanced NumPy • Organizing, documenting, and distributing scientific code • Advanced scientific Python: context managers and generators • Writing parallel applications in Python • Profiling and speeding up scientific code with Cython and numba • Programming in teams
• Caterina Buizza, Personal Robotics Lab, Imperial College London, UK • Jenni Rinker, Department of Wind Energy, Technical University of Denmark, Roskilde, Denmark • Juan Nunez-Iglesias, Bioimage Analysis Research Fellow, Monash University, Australia • Nelle Varoquaux, Department of Statistics, UC Berkeley, CA, USA • Pamela Hathway, Neural Reckoning, Imperial College London, UK • Pietro Berkes, NAGRA Kudelski, Lausanne, Switzerland • Rike-Benjamin Schuppner, Institute for Theoretical Biology, Humboldt-Universität zu Berlin, Germany • Stéfan van der Walt, Berkeley Institute for Data Science, UC Berkeley, CA, USA • Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin, Germany
For the German Neuroinformatics Node of the INCF (G-Node), Germany:
• Tiziano Zito, Department of Psychology, Humboldt-Universität zu Berlin, Germany • Caterina Buizza, Personal Robotics Lab, Imperial College London, UK • Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw, Poland • Jakob Jordan, Department of Physiology, University of Bern, Switzerland
For the University of Camerino, Italy:
• Barbara Re, Computer Science Division, School of Science and Technology, University of Camerino Italy
Website: https://python.g-node.org Contact: firstname.lastname@example.org