STAT 1500
Introduction to Data Science
aims to teach fundamentals of data science. Emphasis will be placed on data visualization, data wrangling and summarizing data, statistical estimation and testing, regression modeling, supervised and unsupervised statistical learning. Standard data science software will be used to demonstrate the techniques.
Prerequisites & course information
PR: 3 credit hours in Mathematics or Statistics courses, or a combination of placement test and high school Mathematics scores acceptable to the Department
Sources
- Course catalogue ↗2026-2027