2600. Introduction to Data Science and Engineering
3.00 credits
Prerequisites:
Grading Basis: Graded
Introduction to a broad selection of challenges and methodologies in working with big data. Topics to be covered include fundamental data science lifecycle topics such as data acquisition, management, integration, visualization, modeling, analysis, prediction, as well as data security, data privacy and ethics.
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