11ᵗʰ Advanced Scientific Programming in Python
==============================================
a Summer School by the G-Node and the University of Camerino

https://python.g-node.org

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 Mathematica 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: see how far we got in previous years 
<https://python.g-node.org/wiki/archives#stats>!

Date & Location
===============
3–8 September, 2018. Camerino, Italy.

Application
===========
You can apply online: https://python.g-node.org/wiki/applications
Application deadline: 23:59 UTC, 31 May, 2018. 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.

Program
=======
• Version control with git and how to contribute to open source projects with 
GitHub
• Best practices in data visualization
• Organizing, documenting, and distributing scientific code
• Testing scientific code
• Profiling scientific code
• Advanced NumPy
• Advanced scientific Python: decorators, context managers, generators, and 
elements of object oriented programming
• Writing parallel applications in Python
• Speeding up scientific code with Cython and numba
• Memory-bound computations and the memory hierarchy
• Programming in teams

Also see the detailed day-by-day schedule: 
https://python.g-node.org/wiki/schedule

Faculty
=======
• Ashwin Trikuta Srinath, Cyberinfrastructure Technology Integration, Clemson 
University, SC USA
• Jenni Rinker, Department of Wind Energy, Technical University of Denmark, 
Roskilde Denmark
• Juan Nunez-Iglesias, Melbourne Bioinformatics, University of Melbourne 
Australia
• Nicolas P. Rougier, Inria Bordeaux Sud-Ouest, Institute of Neurodegenerative 
Disease, University of Bordeaux France
• Pietro Berkes, NAGRA Kudelski, Lausanne Switzerland
• Rike-Benjamin Schuppner, Institute for Theoretical Biology, 
Humboldt-Universität zu Berlin Germany
• Tiziano Zito, freelance consultant, Berlin Germany
• Zbigniew Jędrzejewski-Szmek, Red Hat Inc., Warsaw Poland

Organizers
==========
For the German Neuroinformatics Node of the INCF (G-Node) Germany:

• Tiziano Zito, freelance consultant, 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 
Switzerland

 For the University of Camerino Italy:

• Flavio Corradini, Computer Science Division, School of Science and 
Technology, University of Camerino Italy
• Barbara Re, Computer Science Division, School of Science and Technology, 
University of Camerino Italy


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