Life and physical scientists increasingly use big and complex datasets to answer questions about society and the natural world. In this course, students will develop introductory programming knowledge and data acumen to explore topics drawn from biology, chemistry, physics, and psychology. Students will learn to create and run computer programs, organize ideas using data to communicate clearly to others, break a complex problem into simpler parts, apply general data science principles to specific cases, distinguish causation from correlation and coincidence, and negotiate tradeoffs between different computational and statistical approaches. What new insights about literary form, history, or culture might we glean from a spreadsheet of bestsellers, a database of fan fiction, or an archive containing more novels than any individual could ever read? What gaps exist in literary datasets, and what biases are enshrined in code? No programming or statistical experience required or expected.
Life and physical scientists increasingly use big and complex datasets to answer questions about society and the natural world. In this course, students will develop introductory programming knowledge and data acumen to explore topics drawn from biology, chemistry, physics, and psychology. Students will learn to create and run computer programs, organize ideas using data to communicate clearly to others, break a complex problem into simpler parts, apply general data science principles to specific cases, distinguish causation from correlation and coincidence, and negotiate tradeoffs between different computational and statistical approaches. What new insights about literary form, history, or culture might we glean from a spreadsheet of bestsellers, a database of fan fiction, or an archive containing more novels than any individual could ever read? What gaps exist in literary datasets, and what biases are enshrined in code? No programming or statistical experience required or expected.
