Data Science I with R

Course Director: Mila Sun, PhD, MS

This is a practical introductory course in R programming and unsupervised learning. Students will learn to create clear and effective visualizations, manipulate and summarize complex datasets, and develop interactive tools for data exploration. This course covers foundational topics in unsupervised learning, including dimension reduction, clustering methods, and matrix factorization with illustrative applications. The primary goal of this course is to equip students with the skills and conceptual understanding needed to explore data structure, identify patterns, and critically apply unsupervised learning methods in practice.