CSCI 108 — Foundation of Data Science
Units: 4 Lecture Hours: 54 Lab Hours: 54 Outside Hours: 108 Grading Method: Letter Credit Status: Credit, degree applicable Conditions of Enrollment: Prerequisites: MATH 65 or MATH 73 or MATH 80 with a minimum grade of C or placement into transfer-level math. This course examines the foundation of data science from three perspectives: interferential thinking, computational thinking, and real- world relevance. The course combines programming skills and statistical inference to ask questions and explore problems encountered in real-world datasets, from multiple fields of study, career paths, and everyday life. It also delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership. Note: Only offered in fall.