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Teaching Computation in Neuroscience: Notes on the 2019 Society for Neuroscience Professional Development Workshop on
William Grisham1, Mathew Abrams2, Walt E Babiec3
1Department of Psychology, UCLA, Los Angeles, CA, 90095-1563.
Abstract:
The 2019 Society for Neuroscience Professional Development Workshop on Teaching reviewed current tools, approaches, and examples for teaching computation in neuroscience. Robert Kass described the statistical foundations that students need to properly analyze data. Pascal Wallisch compared MATLAB and Python as programming languages for teaching students. Adrienne Fairhall discussed computational methods, training opportunities, and curricular considerations. Walt Babiec provided a view from the trenches on practical aspects of teaching computational neuroscience. Mathew Abrams concluded the session with an overview of resources for teaching and learning computational modeling in neuroscience.
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