| HUMN 2B31 Computational History & Theory: Data, Science & Machines 0.50 Credit(s) Academic Course |
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| Prerequisite: 3.0 credits of first-year studio and 1.0 credit of first-year liberal arts & sciences (including the Writing course with a minimum passing grade of 60%). |
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| Data machines in computational science transform information into science and social science knowledge – about disease, environments, human behaviour, traffic patterns, etc. This course studies the history of computational mathematics, computational neuro/cognitive sciences and practitioners, addressing how trends in mathematics and scientific paradigms inform science practices and their social effects. Students will employ critical approaches from science studies, philosophy, and communication to evaluate data's historical evolution, its constraints within modular systems and consumer science literature. The course examines historical and contemporary case studies to see how critical theory can be employed to study data in broader, complex (biological and sociocultural) systems to create meaningful findings for society. |
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| Notes: Priority registration for Digital Futures majors. |
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| Course was last updated September 25, 2013 - 3:31 PM | |