Peter Yun

Linear Algebra for Computing introduces vectors, matrices, and transformations with a consistent eye toward their later use in graphics, machine learning, and data analysis. Students leave the course able to read and reason about the linear-algebra notation used throughout the 300-level AI and data courses.

Probability & Statistics for Computing gives students the statistical toolkit that later machine learning, data systems, and empirical research coursework assumes: probability distributions, estimation, hypothesis testing, and enough statistical skepticism to question a dataset before trusting it.