QBS 103 Foundations of Data Science
Strong programming and mathematics skills are the crucial foundation for any data scientist. In this course, students will have an introduction to programing in R and review of critical linear algebra and calculus that will serve as the foundation of many of their courses in this program. Students will be exposed to introductory programming practices, data visualization, data wrangling, introductory data analysis, type setting in LaTeX, using GitHub repositories, and High Performance Computing (HPC). During the calculus review, exercises in topics such as linear algebra, sequences and series, and derivatives and integration will be provided.
Mandatory for MS of Epidemiology, Health Data Science, and Medical Informatics students upon matriculation
Students in other programs need instructor approval to enroll.
(1 unit)
Instructor
Dr. Meghan Muse and Dr. Noelle Kosarek
Prerequisite
Calculus, Multivariate Calculus, Linear Algebra. Previous coding experience highly recommended. Instructor or administration permission for non-MS of Epidemiology, Health Data Science, and Medical Informatics students