Data Science (BS) Major Information & Application
Declared Majors Contact:
Associate Professor, Data Science Advisor
General Concerns Contact:
Tatyana Stahler (she/her/hers)
Academic Program Coordinator, DS Pre-Major Advisor
Major Application Dates/Deadlines
- Fall Quarter
- Opens September 21, 2022
- Deadline: October 14 5:00 PM
- Winter Quarter
- Opens January 3, 2023
- Deadline: February 10 5:00 PM
- Spring Quarter
- Opens March 28, 2023
- Deadline: April 21 5:00 PM
Data Science, BS
Data Science is the study of the mathematical and computational methods for extracting meaning from data. It involves the collection, processing, organization, quantitative analysis, visualization and modeling of data. It is interdisciplinary, drawing from the fields of computer science, mathematics, statistics, and information science, among many others. As data plays an increasingly important role in understanding and discovery across a wide range of disciplines, data science provides a set of tools that enable scholars to better analyze and answer important problems in their own field. In this way, data science often serves as a hub to foster collaboration within and across organizations.
Why consider Data Science?
Data science empowers you to solve important, challenging problems that are otherwise impractical or impossible to solve. These data-centric problems exist everywhere, from science, the arts, business, the humanities and social sciences, engineering and beyond. Today’s world is accumulating data at unprecedented rates, the sheer magnitude of which means that the insights, knowledge, and discoveries buried within that data cannot be found through traditional techniques alone. Algorithms to learn from this data have already revolutionized many fields, from speech recognition to computer vision, producing breakthroughs in artificial intelligence. The skills you will obtain in the Data Science program will enable you to obtain, process, organize, analyze, visualize and model the troves of data out there. Beyond the intellectual satisfaction of data science work, these skills are in high demand. Data science jobs are among the fastest growing in the country, and data scientists often land interesting, challenging and lucrative jobs directly out of college.
How to apply?
Students can apply to the Data Science major once they have completed the pre-major courses, namely CSCI 141, CSCI 145, CSCI 241, CSCI 301, and DATA 311. Data Science pre-major courses have access restrictions during Phase I registration to support enrollment goals and timeliness to degree for Data Science majors.
Admission to the Data Science major is based on many factors, including the student’s academic performance in CSCI 241, CSCI 301, DATA 311, and math readiness. Evidence that the admits will have a positive impact on the department culture is also considered, for example, the student's involvement in clubs, activities, research, volunteering, teamwork, or leadership. Admission is based on a space available basis: neither completion of the prerequisites nor attainment of any specific GPA guarantees admission.
Students may retake at most one of CSCI 241, CSCI 301 or DATA 311 to improve their major application GPA. We make exceptions only in cases of hardship withdrawal from the quarter. Please note that we count late withdrawals as one attempt. Transferred courses do not count in the GPA calculation.
The application to the Data Science major includes an application form and a major declaration e-form. Students should apply to the major by the 5th week of the quarter in which they will complete the pre-major courses. Upon being admitted to the Data Science major students will be assigned an academic advisor from the computer science faculty.
Declaring the Major
Students should apply to the Data Science Major early in the first quarter they are eligible to apply, which is the quarter in which the student is taking or has completed the last of CSCI 241, CSCI 301 and DATA 311.
All applications due by 5:00 PM of deadline.
*Note we do not take submissions during summer.