MAC 5200 Computation in Data Science (ED)
This course introduces students to a range of data-science technologies as well as typical data-science workflows. Students begin with simple exercises involving data ingest, summarization, and visualization, and learning the basics of using the R statistical analysis system. The class then progresses through several foundational data-science technologies, including clustering, association rules, regression, and time-series analysis. The students also work with basic classification technologies, including decision trees, Naïve Bayes, and logistic regression. For use in their future classrooms, students will design two assignments, one as an early assignment in data summarization and one as assignment involving the technology of their choice.