We have 4 video-series, 24 videos and 1 learning-path with the tag scientific.
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Video-series tagged with scientific

Scientific Computing Using SAGE unpingco 04/08 109
Crunchy André Roberge 11/07 84
Scientific and parallel computing using IPython unpingco 04/09 72
Visual Parallel Computing Using Python-based VISION/HPC unpingco 05/09 25

Videos tagged with scientific

Scientific Computing Using SAGE: Introduction unpingco 04/08 58
Two-Dimensional Plots in SAGE unpingco 05/08 49
Introducing and setting up IPython on a Windows PC unpingco 04/09 16
Introducing VISION/HPC unpingco 05/09 15
Using on-line documentation for a short case study on computing integrals unpingco 04/09 10
Basic Parallel Computing Using IPython unpingco 05/09 9
Getting around and using the IPython interpreter unpingco 04/09 7
Closing remarks and using dictionaries effectively for scientific computing unpingco 06/09 6
An Example Using the Imaging Library unpingco 05/09 6
Test Driven Learning (TDL) using Crunchy and MoinMoin. André Roberge 06/08 6
Case Study: Robust Regression Methods Using Python and Parallel IPython unpingco 05/09 4
Getting started with Matplotlib unpingco 05/09 4
Getting Started with Parallel IPython unpingco 05/09 4
Introducing Sympy -- Symbolic Mathematics within IPython unpingco 05/09 4
Using @interact to Add GUI Controls to Computations unpingco 03/10 3
Finer Control for Parallel Computing in IPython unpingco 05/09 3
An Example Using Matplotlib Library unpingco 05/09 3
Case Study: Robust Regression Methods Using Python continued unpingco 05/09 3
Profiling in IPython unpingco 05/09 2
Case Study: Robust Regression Methods Using Python unpingco 05/09 1
Creating customized nodes in VISION/HPC unpingco 05/09 1
Distributing Parallel Computations Using IPython unpingco 05/09 0
Using the IPython Library unpingco 05/09 0
Parallel Computing Using VISION/HPC unpingco 05/09 0

Learning-paths tagged with scientific

Scientific Python Programming [ID:017] Ian Ozsvald, 04/09

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Although as important as the software it supports, education and documentation are relatively neglected in the Open-source world. Coders love to code, and explaining how best to use or improve the software tends to be deferred or even sidelined.

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