Mathematics and Statistics 215: Introduction to Data Science

Credits 4
Credit Type
Semester Offered
Fall: Schueller; Spring: Wirfs-Brock

An introduction to the approaches and tools of exploratory data analysis and visualization. Through a series of projects, we explore large data sets through methods like cleaning, filtering, sorting, boolean selections and merging. As large amounts of data typically are stored in lists, we use algorithmic thinking to transform raw data into usable form. We develop hypotheses and supporting visualizations to tell the story of the data. We learn and practice technical communication in both oral and written form. Through a series of readings and discussions, we learn best practices for the ethical use of data and how to identify problematic uses of data in society. May be elected as Computer Science 215.

Distribution Area
Students entering prior to Fall 2024: Quantitative Analysis (QU DIST)

Mathematics 124 or 125; and Computer Science 167 or 270.