Duke+DataScience (+DS) is a Duke-wide educational initiative devoted to expanding knowledge of and facility with machine learning and other artificial intelligence tools across multiple academic fields, including the arts, humanities, and social sciences as well as medicine and quantitative sciences. With an extensive and growing curriculum that includes both online and in-person courses in neural networks, natural language processing, deep learning, and other machine learning applications, +DS offerings span learning needs ranging from novice to expert and are tailored to specific academic and professional applications.
The spring semester of Duke +Data Science (+DS) Virtual Learning Experiences (vLEs) concluded on May 4th. The Spring 2021 semester attracted over 450 attendances, including people who attended multiple sessions, and comprised 15 unique sessions featuring experts from across many Duke departments. Since its launch in 2018, +DS has held a cumulative 117 learning experience sessions (both in-person and virtual).
In addition to foundational data science and machine learning topics, special topics in spring 2021 included a partnership between
+DS and Duke Science & Society (https://scienceandsociety.duke.edu/) to host a discussion “Recommendation Systems and the Surveillance Economy” which explored the ethical issues surrounding the use of algorithms powering recommendation systems in popular web services.
“Generating Computational Three Dimensional (3D) Geographies” was a humanities workshop that featured an ongoing body of work in computational 3D modeling. The topic revolved around the simulation and rendering of spatial geographic forms, in particular landmasses, landforms, and large-scale geologic features (mountain ranges). The body of work exists both as computational data sets and large-scale visual artworks.
The two-part basic science series “Applying deep learning to biological sequence data” targeted entry-level data scientists. On the first day of the session, participants learned the basics of neural networks and implemented the information learned during a coding session on the following day. The complementary +DS Coursera course is available at https://www.coursera.org/learn/machine-learning-duke
In collaboration with Duke AI Health, +DS launched a new vLE series with the goal of assisting Duke investigators with proposal development in health data science and in sharing experience with the broader Duke community. Attendees enjoyed the conversational nature and discussion between researchers and data scientists. Read more about it here: https://plus.datascience.duke.edu/spring-2021-proposal-studios
The recorded content for the Spring 2021 sessions are archived in the +DS Recorded Experiences Repository here: https://sakai.duke.edu/portal/site/dslearningexperiences (requires Duke credentials to log in).
Tiffany, could you please add a table that includes all of the titles and presenters?
To learn more about the +DS program, please visit https://plus.datascience.duke.edu/