Dear all,

Recently, we organised a Software Carpentry variant for advanced Python users 
[1]. I had the opportunity to present the "Advanced NumPy" lesson, which 
covered a review of basic operations on numpy arrays and also more advanced 
topics: indexing, broadcasting, dtypes and memory layout.

The materials for the lesson are formatted using the SC lesson template [2] and 
are available on github [3]. You can see the generated HTML on github pages 
[4]. 

I estimate that the whole lesson should take around 3-4 hours. The first (and 
so far the only) time I delivered this content it took about 2.5 hours to cover 
the first 5 chapters.

I will be happy to see your comments, pull requests, suggestions etc.

I gratefully acknowledge [5] inspiration, some examples and exercises from the 
following materials:

- NumPy chapters of "SciPy lectures" by Emmanuelle Gouillart, Didrik Pinte, 
Gaël Varoquaux, and Pauli Virtanen [6]
- "Advanced NumPy patterns" by Juan Nunez-Iglesias [7]
- "The NumPy array. A structure for efficient numerical computation." by Stefan 
van der Walt [8]

Yours,

Bartosz

[1] http://telecom-python.telenczuk.pl/ 
[2] https://github.com/swcarpentry/lesson-template
[3] https://github.com/paris-swc/advanced-numpy-lesson
[4] https://paris-swc.github.io/advanced-numpy-lesson/
[5] https://paris-swc.github.io/advanced-numpy-lesson/LICENSE.html
[6] http://www.scipy-lectures.org/
[7] https://github.com/jni/aspp2015/tree/delivered
[8] https://python.g-node.org/python-summerschool-2014/numpy.html
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