Data Science is playing an increasingly foundational role across almost all fields of study at Duke, but many faculty and students whose research and study would benefit from the incorporation of data science lack the necessary skills to take advantage of this rapidly advancing field. +Data Science (+DS) is a Duke-wide program, operating in partnership with departments, schools, and institutes to enable faculty, students, and staff to employ data science at a level tailored to their needs, level of expertise, and interests. +DS provides online (digital) and in-person training modules and learning experiences grounded in generalizable data science content, while partnering with individual units or groups to develop additional specialized content. In this way, Duke’s data science activities will be developed collaboratively, synergistically, and strategically.
A +DS Steering Committee is composed of Robert Caldebank, Tracy Futhey, and Jeff Ferranti. Calderbank is a professor of Electrical & Computer Engineering, Math and Computer Science, and Director of the Rhodes Information Initiative at Duke (iiD). Futhey is the Vice President and Chief Information Officer for the Office of Information Technology. Ferranti is a neonatologist, and serves as the Chief Information Officer in the Duke Health System. +DS partners with many leaders across Duke, including Deans and Institute Directors, to help infuse data science into all Duke educational and research activities.
Leveraging Technology, Reusable Content, and Interdisciplinary Training
+DS leverages and expands several successful activities incubated in the Rhodes Information Initiative at Duke (iiD), specifically Data Expeditions and Data+. For example, Data+, a program in which groups of students work on a data science project for a client, will be expanded into the academic year, and linked with new digital and in-person data-science training. Data Expeditions provides funding for doctoral students who develop a data analytics module in partnership with a faculty member from any division of knowledge/school, who then incorporates the module into an existing course. A key component of the +DS expansion of these programs includes use of technology to summarize outputs from projects, developing a library of content that may be reused subsequently by others at Duke.
+DS manifests vertically integrated teams, composed of students, post docs, and faculty, with each team addressing a data science challenge defined by a dataset and a question. The projects are selected such that a diversity of fields and data types are considered, and importantly they will focus on the most widely applicable and reusable data science methodologies, such as image and video analysis, natural language processing, and other recent advances in machine learning. These projects and programs will also be used for undergraduate and graduate students to complement their degree.
In addition to the aforementioned project-based learning, +DS has developed digital class modules that match the level of math/statistics sophistication to the audience. Data science class modules have been, and will continue to be, developed targeted to diverse units at Duke: from those that only desire a broad understanding of what is possible with data science, to those who wish to understand and use data-science tools (software) without a need for deep understanding of underlying methodology, to finally those who desire a rigorous technical understanding of the details and methodology of data science. Digital course modules will be augmented by regular in-person learning experiences, targeted to a diverse set of Duke audiences.
Duke's Vision of Computational Thinking
+DS is one of the partner programs supporting the mission of the Duke Center for Computational Thinking. Computational thinking at Duke is a transformational way of approaching problems, designing systems, and understanding human expression using fundamental ideas from computational science, and builds on our proven success in engaging and empowering student journeys through interdisciplinarity, project-based experiences, and team-based learning.
Learn +DS Online And In-Person
The online +DS modules introduce Data Science concepts. Review the online content, and explore the in-person +DS opportunities to dive deeper into the information introduced in the online modules.