+DataScience (+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 training modules and learning experiences grounded in generalizable data science content, while partnering with individual units or groups to develop additional specialized content.
The online +DS modules introduce Data Science concepts. They are comprised of summer school video lectures and Coursera at Duke modules. The online content may be viewed in the context of self-learning, but the principal objective of the online +DS modules as previewing prior to in-person learning experiences. In particular, select and specified online +DS modules serve as pre-requisites for in-person learning experiences.
In addition to the aforementioned Coursera content, +DS offers recordings from one of Duke’s Machine Learning Summer School (MLSS), held in June of 2018. If you are a Duke student, staff or faculty member, you can review these classroom recordings on Panopto, with accompanying slides and links to github code demos.
+DS also offers recordings of a series of lunch and learning, held in fall of 2019, about how artificial intelligence (AI) is transforming healthcare. If you are a Duke student, staff or faculty member, you can review these recordings of the sessions, led by both clinical experts and technical experts sharing both the medical context and the technical aspects.
Once you have reviewed the online content, +DS offers in-person and virtual opportunities to dive deeper into the information introduced in the online modules. These learning experiences will be developed to target diverse units at Duke: from those that desire a broad understanding of what is possible with data science, and those who wish to use data-science tools (software) without a need for deep understanding of underlying methodology, to those who desire a rigorous technical proficiency of the details and methodology of data science.