The Ph.D. in Data Science program will provide the essential skills required to analyze big and complex data sets and equip students with a broad understanding of data challenges and opportunities, along with the research and inquiry skills necessary to independently conduct research and answer questions within their area of concentration.
To meet this goal, courses in the Ph.D. in Data Science Program curriculum are organized around interdisciplinary focal areas in computer science, engineering, mathematics, and statistics. Courses offered within this framework include traditional lecture-style, e-learning, and special topics courses that introduce students to the latest theories, methods, and emerging issues; seminar series; and experiential learning. Through this framework, students will gain proficiency in the application of scientific principles such as, critical thinking, experimental design, data preprocessing and wrangling, data visualization, advanced statistical learning/data mining and machine learning, as well as a sense of professional and technical writing, and reporting, responsibility, and integrity.
Students possessing a bachelor’s degree will be required to complete a minimum of 72 semester hours of graduate-level work. Students possessing a master’s degree in a related field will be required to complete a minimum of 42 semester hours of graduate-level work beyond their master’s degree in addition to meeting other Ph.D. requirements in the section below. Up to 30 of the credits earned in pursuit of your master’s degree may be transferable to the Ph.D. program as either core courses or elective courses.
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