Overview of data science key concepts and the use of tools for data retrieval, analysis, visualization, and reproducible research in preparation for advanced data science courses. Topics include an introduction to inference and prediction, principles of measurement, missing data, and notions of causality, statistical traps, and concepts in data ethics and privacy.

Prerequisites: PSTAT 120A; CS 9 or CS 16; and Math 4A, all with letter grade C or better.

4

Units

Optional

Grading

1

Passtime

None

Level Limit

Letters and science

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