This course provides an overview of data science including a foundation in research methodology. Data science is a data-driven process that provides descriptive, predictive, and prescriptive insight. Whether reporting on historical information or making predictions about future events, the goal of data science is to add value through analysis that informs. To meet this goal this course introduces a range of tools and methods including supervised and unsupervised techniques. These include techniques such as classification, rule-based association techniques, support vector machines, K-nearest neighbor, regression, and clustering techniques such as K-Means. (Prerequisite: DATS201)

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