The data science major combines computer science, statistics, and a student's choice of advanced coursework in an application area, such as:
- Biomedical Signals & Imaging
- Brain and Cognitive Sciences
- Earth and environmental science
- Economics & Business
- Political science
Choosing Between a BA and a BS
While many of the requirements between the BA and BS program are the same, BS students must take three additional supplementary courses. With fewer courses, the BA program gives students more flexibility and is usually the preferred choice for students looking to double major. Alternatively, students in the BS program get a more in-depth look at data science.
In order to plan and declare your major, please visit the our advisor in Wegmans Hall. For email inquiries, contact firstname.lastname@example.org.
Through the capstone project our students have the opportunity to work with industries to conduct real-world analytics projects using data provided by sponsoring organizations. Capstone students will work in teams of three to four members over the semester to understand the business problem, clean and analyze the data, and devise a solution. Students also explore ethical issues related to the use of data science.
The capstone project is only available to upper-class students.
Data Science Clubs and Activities
The Data Science Undergraduate Council at UR, also known as UR NoDES, organizes on-campus hackathons, discussions, parties, and other events throughout the year. Visit their FaceBook page for information about the club.
The greater Rochester community has groups that pertains to individuals in data science and are excellent ways for students to network with professionals in the industry. ROC Data Science and Rochester Python (RocPy) are Meetup groups with members from UR, RIT, other local colleges and various businesses. Their talks, tutorials, and discussions are held at various sites around the Rochester area - often at restaurants, coffee shops, company offices, and occasionally on our own campus - are open to anyone interested in data science.
A variety of talks are presented throughout the year that are open for students to attend to learn more about careers and research in data science. They included GIDS Speaker Series, CIRC Symposia Series, and career presentations from alumni and industry.
Support for Studies
The River Campus Libraries provides a collection of resources from the library and services the library provides, as well as helpful information and interesting resources in the LibGuide for Data Science.
You can also contact the data science peer advisor for help with academic studies.
Support for Research
Students who are seeking research should review websites of GIDS affiliated faculty and the related institutes and centers at the university to find research that may be of interest to them. We also advise students to attend research talks on campus such as the monthly CIRC Symposium Series.
UR-UPP is an initiative out of the Office of Undergraduate Research designed to support students in preparation for, pursuit of, and placement in research positions. Submit a Research Interest Inventory to inform them of your research interests and motivations, and UR-UPP will provide advising services targeted to your unique needs and questions. UR-UPP offers supplementary support through the recruitment of available mentors and/or projects in the health/life science, clinical, and computational fields.
Support for Travel
Goergen Institute for Data Science supports our undergraduates for professional development through attendance at events and conferences. Students have attended Grace Hopper Celebration, MIT Sloan Sports Analytics Conference, hackathons and other events. To be reimbursed for related travel, students should submit the student conference travel application 5 weeks or more prior to travel.
The Department of Labor projects a 25 percent growth rate in employment for data scientist and analysts through the year 2018. Also, in a recent survey 76 percent of the 1,400 CIOs surveyed said their companies weren’t gathering customer data such as demographics or buying habits. Among those that were gathering such data, more than half said they lacked sufficient staff to access customer data and generate reports and other business insights from it. (Source: Robert Half Technology. Read more on Forbes.com)