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Training course: "Scientific Python"
From Monday 18 March 2013 -  08:00
To Wednesday 20 March 2013 - 17:00
by  This e-mail address is being protected from spambots. You need JavaScript enabled to view it Hits : 816

Python is being increasingly used in scientific computing as it is easy to make changes and explore new ideas.

Many Python packages support scientific computing. NumPy provides functionality for working with arrays. SciPy contains functionality for performing common tasks on these arrays, for example linear algebra, optimisation, numerical integration, and much more. Matplotlib is used to produce publication-quality plots.

The course will begin with an overview of NumPy and SciPy and then work along examples targeted at people interested in Python's capabilities and potential applications in their fields.


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Location : Ausbildungsraum 2, Jülich Supercomputing Centre, building 16.3, room 004