All courses, faculty listings, and curricular and degree requirements described herein are subject to change or deletion without notice.
Data science refers to mathematical models, computational methods, and analysis tools for navigating and understanding data and applying these skills to a broad and emerging range of application domains. A whole range of industries—from drug discovery to healthcare management, from manufacturing to enterprise business processes as well as government organizations—are creating demand for the “data scientist” with a skill set that includes a combination of computer programming, statistical analysis, and machine learning. Such a professional can create mathematical models of data, identify trends and patterns using suitable algorithms, and present the results in effective manners. The target systems can be biological (e.g., clinical data from cancer patients), physical (e.g., transportation networks), social (e.g., social networks), or cyber-physical (e.g., smart grids). In all these cases, the core knowledge base of the data scientist is the same and lies at the intersection of computing and mathematics, coupled with the skills to abstract, build, and test predictive and descriptive models. Depending upon the application domain, these capabilities often require a good understanding of underlying areas of physical or biological sciences as well as human cognition.
The major consists of 116 units; some lower-division courses be may used to fulfill general-education requirements. The required courses include mathematics (especially linear algebra and probability), computer science (programming, data structures and abstractions, and data mining), and statistics (estimation, testing, and exploratory data analysis). A twelve-unit lower-division course sequence in physics, chemistry, or biology will strengthen a major’s background in natural and physical sciences. The program includes twenty units of elective courses that will enable students to embark upon an in-depth exploration of one or more areas in which data science can profitably be applied. Alternatively, students can choose to explore the mathematical, statistical, and computational foundations of data science in even greater depth.
All majors will be required to undertake a senior project that will give them an opportunity to creatively synthesize much of what they have learned in the data science courses for addressing problems in chosen domains.
Students are expected to complete the following fifty-six units by the end of their sophomore year. All courses must be taken for a letter grade and passed with a minimum grade of C–.
Students must complete sixty upper-division units. All courses must be taken for a letter grade unless offered Pass/Not Pass only. A minimum grade of C– is required.
This minor is intended for students whose primary area of interest lies outside data science, but who are interested in acquiring competence in methods of data analysis. It requires completion of fifty-six units. Courses must be taken for a letter grade with a minimum passing grade of C–.