DATSC-BA - Data Science (BA)

Mission of the Undergraduate Program in Data Science 

The mission of the undergraduate program in Data Science is to provide students with an analytical and quantitative foundation for tackling data-driven problems in science, industry, and society. Data science is an interdisciplinary field that combines computational and inferential reasoning to extract knowledge or insights from data for use in a broad range of applications. It synthesizes the most relevant parts of foundational disciplines in order to solve particular classes of problems or applications.  As more data and new ways of analyzing data become available, our economy, society, and daily life will become even more dependent on our ability to systematically learn from data.  

Students pursuing the B.A. in Data Science and Social Systems will develop a rigorous understanding of methods and approaches from computer science, statistics, and the social sciences, and will learn to apply technical tools to address substantive problems in that domain. They will develop multiple fluencies: in computational methods, in the domain knowledge and applications of social science broadly, and in the moral and political frameworks that shape social systems. The B.A. in Data Science and Social Systems is an ideal major to prepare students for work in the technology sector and a range of industries that require integrating quantitative thinking with an understanding of human behavior or public policy, or for careers in the public and social sectors where data-intensive approaches are prized.

B.A. Degree Requirements

Data Science and Social Systems majors will complete an introductory course, courses in a set of core areas, a practicum in which they apply data science skills to a well-defined problem, and a pathway in a particular area of concentration. To declare this major, students should select the B.A. in Data Science and the Social Systems subplan. There are three parts to the core: quantitative (math, computation, statistics, and optimization), behavioral science (psychology, sociology, political science, and economics), and ethics. In addition, the introductory course to the major and the capstone will provide students with real-world examples and opportunities to apply modern computational and statistical techniques to address key social challenges. Interdisciplinary thinking is essential for data-driven analysis of complex social problems, and the program is designed to prepare students with superb technical training and in-depth knowledge of the social sciences.