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Nov 22, 2024
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Academic Bulletin 2023-2024 [ARCHIVED CATALOG]
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CMPSC 301 - Data Science
Credits: 4
A study of computational methods of data analysis with an emphasis on understanding and reflecting on the social, cultural, and political issues surrounding data and its interrogation. Participating in hands-on activities that often require teamwork, students study, design, and implement analytics software and learn how to build predictive models with foundational machine learning algorithms to extract knowledge from various sources of data. Students also investigate the biases, discriminatory views, and stereotypes that may be present during the collection and analysis of data, reflecting on the ethical implications of using the resulting machine learning techniques. During a weekly laboratory session, students use industry-grade open source statistical software to complete projects, reporting on their findings through both written documents and oral presentations. Students are invited to use their own departmentally approved laptop in this course; a limited number of laptops are available for use during class and lab sessions.
Prerequisite: CMPSC 101 or CMPSC 102 .
Distribution Requirements: QR, PD.
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