Data Visualization and Analytics

Catalog description

This course explores advanced techniques for visualizing and analyzing complex datasets, including point-in time, time-series, spectral, and image data. Students will enhance their exploratory data analysis (EDA) and data cleaning workflows to transform raw information into insights for communication and decision making. A component of this course will focus on creating interactive visualizations (e.g., dynamic plots, Shiny applications, and 3D models). The goal of the course is to develop data visualizations that are tailored for diverse audiences. A mixed reality component is included in this course so students learn to develop visualizations within an immersive environment. Beyond technical skills, the course examines the ethics of data representation and the theory of how audiences interpret information. This course uses a Git repository, open-source resources, and reproducible data science tooling. Offered as DSCI 354 , DSCI 354M , and DSCI 454 . Prereq: ( DSCI 351 or DSCI 351M ) and ( DSCI 353 or DSCI 353M ).