Students trained in Data Science will study a blend of topics from many subdomains of communications, philosophy, mathematics, computer science, and information science. A data scientist has a breadth of experience across all of these fields, but may not have as much knowledge as a specialist in any particular field. Furthermore, a data scientist trained at William & Mary is equipped to consider the philosophical and moral implications of algorithm development and data collection, and the societal ramifications that new approaches to data manipulation could have. This combination allows William and Mary Data Science students to (a) efficiently conduct computational analyses within their own knowledge domain, (b) manage teams of more specialized individuals to answer far-ranging questions, and (c) communicate technical findings to new types of audiences. Individuals with this set of knowledge are revolutionizing a wide set of domains, and are in very high demand not just by faculty researchers at William and Mary, but also by the public and private sector.
The College of William and Mary offers a minor in Data Science, which draws on faculty expertise from many departments. There are four key pedagogic pillars students will be expected to engage with during their time in the program: Computation, Application, Communication, and Deliberation.
Computation - the computer science and mathematics required to responsibly use large datasets to create new knowledge. This is a focus of the introductory coursework, as well as the elective data specialties.
Application - the skills and creative thinking required to identify novel ways to apply computation to new problems. Application is present in all core courses within the Data Science program, including CSCI 140, CSCI 146, and APSC 490 Data Driven Decisionmaking.
Communication - the confidence to present in front of a crowd, and creativity to communicate or visualize technical concepts for new, likely non-technical audiences. Courses such as public speaking and art help promote such confidence and creativity; while many students will naturally receive some communications training as a part of their time at William and Mary, the Data Science program promotes an additional depth of skill due to the challenges in communicating large sets of data. Communication is a strong theme within all Data Science core courses.
Deliberation - the ability to consider the societal, moral, and ethical implications of Data Science. Data Science minors are required to take either a College 150 examining these topics or broader philosophy coursework.
The Data Science minor is designed to be paired with a wide variety of majors across William & Mary, so there are no restrictions on the primary major pursued in conjunction with the Data Science minor. Under most circumstances the Data Science minor should be declared no later than the second semester of the Junior year to ensure the minor can be completed. Two courses may be counted toward both your primary major and minor; some courses may be substituted with permission from the director. In addition to the required work, various other courses as well as non-classroom training (such as internships, research projects with faculty, participation in study abroad programs, or off-campus study) are strongly recommended. For further questions, contact the program Director (Prof Dan Runfola; Applied Science - email@example.com), or reach out to one of the Faculty Affiliates listed at ds.wm.edu.