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Data Science is a dynamic and fast growing field at the interface of Statistics and Computer Science. The emergence of massive datasets containing millions or even billions of observations provides the primary impetus for the field. Such datasets arise, for instance, in large-scale retailing, telecommunications, astronomy, and internet social media. This course will emphasize practical techniques for working with large-scale data. Specific topics covered will include statistical modeling and machine learning, data pipelines, programming languages, "big data" tools, and real world topics and case studies. The use of statistical and data manipulation software will be required. Course intended for non-quantitative graduate-level disciplines. This course will not count towards degree requirements for graduate programs such as Statistics, Computer Science, or Data Science. Students should inquire with their respective programs to determine eligibility of course to count towards minimum degree requirements. This course does not fulfill any major requirements for undergraduate degree programs offered by Computer Science.
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