Mo(Wa)²TER Introduction to Data Science Course Material

These are the materials developed for the Mo(Wa)²TER Introduction to Data Science Course, which is designed for undergraduate students from any background. Introduction to principles of data science in R, including problem workflow, variable types, visualization, modeling, programming, data management and cleaning, reproducibility, and big data are provided. Real examples and exercises are given with each topic to strengthen and deepen comprehension. These materials aim to inspire students to pursue additional data science training to prepare them for their future careers. Materials were developed over three offerings of this course in 2020, 2021, and 2022. The course was designed with a flipped structure wherein students watched a series of short videos of the instructor explaining the lecture notes before class, and class time was spent on completing the in-class exercises. At the time of publication, all code runs, but we provide no guarantees on future versions of R or packages used in this course.