The Data Dilemma

Data now come in all shapes and sizes, from -omics data and images to electronic health records and everything in between. These data provide great opportunities for learning policies and clinical strategies that can improve health outcomes, but they also come with unique challenges. Today’s public health researcher needs quantitative and computational training to understand these diverse data.

At Rollins, interest in advanced quantitative and computational skills has risen exponentially over the past several years. To meet the demand from students, and to contribute to the growing needs in the field, Rollins has been expanding its course offerings in these areas as well. This fall, the school is launching a new Data Science Certificate for enrolled master’s students. Facilitated by the Department of Biostatistics and Bioinformatics, the program is open to students across academic departments at Rollins.

“We are hoping that this certificate will help our students obtain the set of skills needed to contribute to the field during this exciting time,” says David Benkeser, PhD, associate professor of biostatistics and bioinformatics and director of the certificate program.

Students interested in enrolling in the certificate program are required to submit a declaration of interest form. No prerequisites are required and, as Benkeser notes, the program was intentionally designed to make it accessible to students across the school.

Filling the Gap

“Rollins faculty have long been at the cutting edge of public health research, and we’ve offered courses along these lines for some time, but in the past, we’ve lacked the sort of structure to make sure that students were supported and advised during their training experience,” says Benkeser.

“Our workforce needs to keep up with the demands of modern health research,” he adds. “This requires a set of skills that has been lacking in the job market. Because the field is advancing so quickly, it is difficult for working professionals to keep pace with developments in these fields. The goal of the certificate is to augment the existing classical public health training that students receive at Rollins with a set of skills that allow them to fill this gap.”

Students enrolled in the program complete four required courses (Introduction to R Programming for Non-BIOS Students or R Programming for BIOS Students, Data Science Toolkit, Machine Learning or Applied Machine Learning in Public Health, and Current Topics in Data Science), plus three to four hours of related elective credits. Certificate students also complete a data science-related applied practice experience, or three additional credit hours related to data science and an integrated learning experience.

“Our students need education and training to be prepared to face a new world where they are unlimited by the amount of information they can access,” says Yang Liu, PhD, chair and Gangarosa Distinguished Professor of Environmental Health. “That abundance of information and knowing how to make sense of the huge amount of very noisy data require a very different mindset—one that is critical to the future of public health.”

Liu notes that with a stronger emphasis on data science at Rollins, he expects to see a shift in the type of students attracted to advanced degrees in public health, including engineering students and hard science students.

“A projected continued explosion in the volume, complexity, and diversity of health data makes individuals with a combination of cutting-edge data scientific skills and a foundational understanding of public health principals essential to the future of the field,” says Robert Krafty, PhD, chair of the Department of Biostatistics and Bioinformatics. “This Data Science Certificate program will not only train students to be successful in today’s workforce but will also train the next generation of leaders who will shape the future of public health.”