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Curriculum

The PhD in Big Data Analytics is built on an interdisciplinary infrastructure that draws from expertise across USF. Students entering the program will take core courses during the first two years of study. These core courses reach across several different colleges and include coursework in mathematics and statistics, computer science and engineering, industrial and management systems engineering, psychology, public health and business. In addition to core courses, students will also have the ability to take elective courses depending on their specific areas of interest.

After the second year of study, students complete their qualifying exam. During this exam, students report on the results of a real-world, large-scale data analytics project in the form of a research paper accompanied by code/systems that were developed. The paper (and code/programs) are submitted to and evaluated by a committee of interdisciplinary faculty members. After successful completion of the qualifying exam, students will be admitted to candidacy, select a dissertation committee and eventually defend the dissertation in front of that committee.

The complete curriculum can be found in the catalog at this . 

 

Cohort-Based Activities

Given that this is an interdisciplinary program where doctoral students may branch out in different directions (both in terms of course choices they make as well as in terms of the domain of their research), the program includes activities required of all students that help foster, maintain and leverage a strong sense of community as a 鈥渃ohort.鈥� These include:

• Joint research seminars. Doctoral students in this program participate actively in not- for-credit research seminars as a cohort on a regular (biweekly) basis. Attendance and participation in such seminars will be included in the student鈥檚 progress toward degree annual evaluation. Students will be permitted to register for a three-credit, independent-study course to obtain credit for attending these joint research seminars should they wish (this option will be useful for those who need the flexibility this affords to complete coursework sooner).
• Advisory committee meetings. Students meet with their Doctoral Advisory Committee members (comprised of interdisciplinary faculty across different colleges) every semester. There will also be one combined meeting every year to bring all students together to share experiences and current research plans, so that the feeling of a cohort is strengthened  while  allowing students to learn from each other鈥檚 experience in the program.

Teaching Component

Students are strongly encouraged to obtain teaching expertise during their course of study, especially those who intend to apply for an academic position. Applicants who aim for academic positions will be encouraged to apply for assistantships where teaching is a component.