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Video: A Computational Future for Science Education

Kathryn D. Huff, Berkeley Institute for Data Science

Kathryn D. Huff, Berkeley Institute for Data Science

In this video, Katy Huff from the Berkeley Institute for Data Science presents: A Computational Future for Science Education.

“Detailed computational models, massively parallelized calculations, and enormously collaborative simulation projects are increasingly integral to the advancement of science. However, the caliber of this work is limited by a workforce lacking formal training in a reproducible, transparent, software development skill suite that is becoming increasingly essential. To address this unmet need, a number of initiatives (e.g. Software Carpentry, Data Carpentry, and The Hacker Within) have developed online resources, led short courses, and nurtured local communities addressing software development best practices such as version control and test driven code development, as well as basic skills such as UNIX mobility. In addition to unique contributions such as a “Driver’s License for High Performance Computing,” Software Carpentry conducts workshops at research institutions around the world. These workshops seek to provide time efficient introductions to essential programming languages and tools without turning “biochemists and mechanical engineers into computer scientists.” The Hacker Within similarly nurtures a peer-driven community for scientific computing skill sharing. It does so through regular meetings in a few local chapters around the world, including one at the University of Illinois.

The scalability and sustainability of these initiatives, however, is limited by the volunteer power on which they run, so their challenge will only be sustainably solved when best practices in scientific computing have penetrated the traditional science and engineering curriculum in universities. This talk will describe one new effort to embed best practices for reproducible scientific computing into traditional university curriculum. In particular, a set of open source, liberally licensed, IPython (now Jupyter) notebooks are being developed and tested to accompany a book “Effective Computation in Physics.” These interactive lecture materials lay out in-class exercises for a project-driven upper-level undergraduate course and are accordingly intended to be forked, modified and reused by professors across universities and disciplines.”

View the Slides

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