[ANN] 11ᵗʰ Advanced Scientific Programming in Python in Camerino, Italy, 3—8 September, 2018
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11ᵗʰ Advanced Scientific Programming in Python ============================================== 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 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.
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
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