Undergraduate Programs

Major and Minor in Data Sciences

The goal of these programs is to train a generation of students who are equally versed in predictive modeling, data analysis and computational techniques. 

The undergraduate major in Data Science will prepare our students for a career in the data-centric society and to advance knowledge in the emerging field of Data Science.

Data Sciences Major

The major consists of 116 units in addition to general education requirements, some of which may be covered by the major. The required courses include courses in mathematics (especially linear algebra and probability), computer science (programming, data structures and abstractions, data mining), and statistics (estimation, testing, and exploratory data analysis).

A 12-unit lower division course sequence in physics, chemistry or biology will strengthen background in natural sciences. The program includes 20 units of elective courses that 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 two-quarter senior project that will give them an opportunity to creatively synthesize much of what they have learned in their courses.

The major is modeled after our successful interdisciplinary programs in computer engineering and bioinformatics/systems biology across multiple departments and divisions. Administratively, the program will be overseen by a coordination committee drawn from representatives across the participating departments under the purview of one or more cognizant deans.

Data Sciences Minor

Beginning in Fall 2017, students can declare a minor in data sciences from other participating departments. The minor might include, for instance, students of literature who are interested in conducting statistical analyses of digital corpora, or psychology majors who wish to conduct large-scale human subject experiments using crowd sourcing, or business and economics students who need to understand computational and statistical methods for analyzing market and customer preference data. The minor will provide basic training in computer programming, linear algebra, as well as probability and statistics, and a high-level overview of the different types of data and the methodologies appropriate to each. By the end of the minor, they will be able to write programs that preprocess data suitably, and that invoke a variety of signal processing, statistics, and machine learning subroutines to extract meaning from the data. Going beyond participation in offering minors, the coordination committee will encourage participation of additional departments in creating data science related majors that are specific to their domain needs.

Program Coordinator/Undergraduate Advisor
Margaret Zuhlke

Intake Advisor
Meaghan Kelliher