L&S Data Science Major

Objectives

Data Science combines computational and inferential reasoning to draw conclusions based on data about some aspect of the real world. Data scientists come from all walks of life, all areas of study, and all backgrounds. They share an appreciation for the practical use of mathematical and scientific thinking and the power of computing to understand and solve problems for business, research, and societal impact.

The Data Science Major will equip students to draw sound conclusions from data in context, using knowledge of statistical inference, computational processes, data management strategies, domain knowledge, and theory. Students will learn to carry out analyses of data through the full cycle of the investigative process in scientific and practical contexts. Students will gain understanding of the human and ethical implications of data analysis and integrate that knowledge in designing and carrying out their work.

major structure

Description of the Undergraduate Major

The L&S undergraduate Data Science major requirements include one core lower-division (Data 8) and upper-division (Data 100) course, along with required courses from each of the following groups:

  • Foundations in Mathematics and Computing
  • Computational and Inferential Depth
  • Modeling, Learning and Decision Making
  • Probability
  • Domain Emphasis
  • Human Contexts and Ethics