Dr. Jon Bannon, Program Coordinator
Data Science Faculty Steering Committee: Dr. Matthew Bellis, Dr. Eric Breimer,
Dr. Scott Greenhalgh, Dr. Mary Beth Kolozsvary, Dr. Ting Liu, Dr. Graziano Vernizzi
Data science is an emerging multidisciplinary field that uses a synthesis of computer science, mathematical and statistical techniques to gather, analyze, and visualize large data sets in order to extract new knowledge for decision making. A command of the subject matter related to the data in order to be able to ask the right questions.
A student graduating from this program will demonstrate sensitivity to data science as a liberal art. The program aims to immerse students in thinking about the pervasive volume of structured and unstructured data and its meaning for contemporary life in a broad sense aligned with the aims of the classical liberal arts, and not as a simple list of specific vocational and technical skills without application to society. Emphasis is on the development of students’ capacity to imagine possible solutions to problems of importance to humanity. This need for knowledge of a specific subject area is addressed by the specialty areas of study available to the data science students that are described below. Students can also choose an internship/engagement experience through which they will apply their knowledge beyond Siena or deepen it through a guided independent study. Graduates from this program will have training and experience in finding patterns in immense data streams; these skills are applicable in business, the natural and social sciences, and many other fields.
A student planning to major in data science should contact the program coordinator, or any other member, of the Faculty Steering Committee (FSC). Not every course is offered every year, so care must be taken in scheduling to assure completion of the major. The B.S. in Data Science includes a core of essential courses needed to gain both depth and breadth of knowledge for careers or graduate study in the field of data science. Students can then pursue two distinct tracks: the Data Science Track, which includes additional coursework in mathematics, computer science, and a two-course sequence in a laboratory-based science, to strengthens students’ understanding of the scientific method and to provide breadth of knowledge in a field relevant to data science; or the Applied Data Science Track, which includes additional coursework in a cognate area where students can focus on applying their data science knowledge.
ProgramsBachelor of ScienceMinor