DATSC-BS - Data Science (BS)

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.S. in Data Science will acquire a core foundation of mathematics basic to all the mathematical sciences and be introduced to concepts and techniques of computation, optimal decision making, probabilistic modeling and statistical inference. Beyond this foundation, students can explore how inferential and computational thinking can be effective in areas as diverse as finance, biology, marketing, and engineering; or they can choose to acquire greater depth in one of our core disciplines. The B.S. in Data Science is an ideal major to prepare students for graduate study in quantitative fields such as computer science and statistics, and for careers in a range of industries that require quantitative work, such as information technology and finance.

B.S. Degree Requirements

The Data Science program is interdisciplinary in its focus, and sponsored by Stanford’s departments of Statistics, Mathematics, Computer Science, and Management Science & Engineering.  Students are required to take courses in each of these departments. A computational biology track is available for students interested in applications of mathematics, statistics, and computer science to the biological sciences (bioinformatics, computational biology, statistical genetics, neurosciences); and in a similar spirit, there are engineering and statistics options.