Data Science

The Program in Data Science provides students with an analytical and quantitative foundation for tackling data-driven problems in science, industry, and society. As an inherently interdisciplinary field, data science combines computational and inferential reasoning to extract critical knowledge or insights from data for use in various real-world applications.

By synthesizing the most relevant aspects of foundational disciplines, our program teaches students how to systematically analyze, interpret, and learn from data. As our economy, society, and daily life become increasingly dependent on data-intensive systems, our graduates emerge equipped with the technical competence and critical perspective needed to lead in a data-centric world.

Academic Programs and Quantitative Pathways

The Program in Data Science offers multiple undergraduate pathways designed to develop computational fluency, critical analysis, and technical expertise:

• Bachelor of Science (B.S.) in Data Science: Provides a core foundation in mathematical sciences, computation, optimal decision-making, probabilistic modeling, and statistical inference. Students explore how inferential and computational thinking apply to areas as diverse as finance, biology, and neuroscience, or they can choose to acquire greater depth in the core disciplines. This major trains nimble and versatile data scientists, and provides ideal preparation for careers in technology and finance, or graduate study in quantitative fields like computer science and statistics.

• Bachelor of Arts (B.A.) in Data Science and Social Systems: Develops a rigorous understanding of methods from computer science, statistics, and the social sciences. Students learn to apply technical tools to complex social  problems, building multiple fluencies in computational methods, social science domain knowledge, and the moral and political frameworks that shape human behavior and public policy. This major prepares students for careers in technology, government, the non-profit sector, and industries requiring the integration of quantitative thinking with an understanding of social systems.

• Bachelor of Arts (B.A.) in Data Science for Artistic and Cultural Analysis: Integrates comprehensive data science methods and theories with the core critical thinking and creative skills of humanistic study and artistic practice. Students apply quantitative and statistical methods to study cultural and aesthetic objects, explore how data alters our understanding of history, practice integrating computation into the creative process, and think critically about the role of data in society, culture, and the arts. This major prepares students for industries where data science, creative thinking, and critical problem-solving are highly valued.

Methodological Foundations and Multi-Domain Integration

Data Science at Stanford is characterized by its broad integration across traditional disciplinary boundaries, applying rigorous computational and statistical methods to diverse scientific, social, and humanistic questions:

• Computational and Inferential Reasoning: Leveraging mathematical models, probability, and advanced computational techniques to systematically extract insights from complex datasets.

• Social Systems and Ethical Frameworks: Integrating statistical and computational methods with the social sciences and ethics to understand human behavior and social systems and address challenges responsibly. 

• Aesthetic and Cultural Analysis: Utilizing computational tools to analyze historical trends, artistic productions, literature, philosophy, and visual media, bridging the gap between quantitative science and humanistic exploration.