Data Science (DATA)

DATA 060: Data Visualization (3 Credits)

This course teaches skills for seeing and showing the information in data. We will draw on principles of design, human perception, color theory, and storytelling to develop standards of data visualization, and we will learn a range of tools for implementing them. Topics include the history of diagrams, charts, maps, and graphic design; theories of aesthetics and the psychology of perception; static, dynamic, and interactive displays of data; data journalism; visualization of social media and marketing data; 3D visualization.

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DATA 60: Data Visualization (3 Credits)

This course teaches skills for seeing and showing the information in data. We will draw on principles of design, human perception, color theory, and storytelling to develop standards of data visualization, and we will learn a range of tools for implementing them. Topics include the history of diagrams, charts, maps, and graphic design; theories of aesthetics and the psychology of perception; static, dynamic, and interactive displays of data; data journalism; visualization of social media and marketing data; 3D visualization.

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DATA 150: Introduction to Data Analysis (4 Credits)

Data analysis is the extraction of knowledge and insights from complex data. This course introduces the concepts, issues, and techniques of data analysis. Topics include data cleaning and preparation, feature selection, association rules, classification, clustering, evaluation and validation. Tools implemented in R and Python will be used to explore data sets using these techniques.

Prerequisite(s): CS 064 and MATH 102

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