Tools in Data Science

Description: Lecture, three hours; discussion, one hour. Requisites: courses 404, 405. Limited to Master of Applied Statistics students. Tools for data acquisition, transformation and analysis, data visualization, and machine learning and tools for reproducible data analysis, collaboration, and model deployment used by data scientists in practice. Advanced R packages, analytical databases, high-performance machine learning libraries, big data tools. S/U or letter grading.

Units: 4.0
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