Announcements + Events

August 22, 2019

Duke’s Plus Data Science (+DS) program invites you to learn about how artificial intelligence (AI) is transforming healthcare through a series of lunch and learns this fall.

Topics will include deep learning for digital pathology, neural networks and retinal image analysis, machine learning approaches for autism screening, and natural language processing with communications between patients and clinicians.

August 22, 2019

The +DS in-person opportunities dive deeper into the basics of data science across multiple important application domains. These learning experiences are developed to target diverse units at Duke: from those that desire a broad understanding of what is possible with data science, those who wish to use data-science tools (software) without a need for deep understanding of underlying methodology, and those who desire a rigorous technical proficiency of the details and methodology of data science.

The +DS In-Person Learning Experiences for September are:

July 16, 2019

This past June, more than 100 participants filled the Schiciano Auditorium in the Fitzpatrick Center for Interdisciplinary Engineering, Medicine and Applied Sciences (FCIEMAS) on Duke University’s West Campus. They were there to attend the latest offering of Duke’s innovative Machine Learning School program.

June 10, 2019

Students, faculty, and staff from across Duke recently assembled for the Data Science Student Showcase, held at the Gross Hall Atrium on the morning of April 25th. Put together by the +DS Projects in Medicine and the DCRI-Forge HDS Internship Program, the event served as a platform for students to present the  projects that they have been immersed in during the spring semester.

April 30, 2019

The Duke Machine Summer Learning School will be offered June 17-21, 2019 focusing on the areas of machine learning that have made the biggest advances in utility over the last several years, including deep learning. The class will concentrate on methods that allow machine-learning algorithms to train effectively on massive datasets, i.e., “big data.” Emphasis will be placed on the latest methods for image and video analysis, natural language processing, reinforcement learning, and data synthesis/modeling.

April 15, 2021 - 5:00 pm to 6:30 pm
April 16, 2021 - 10:00 am to 11:30 am
April 16, 2021 - 2:00 pm to 4:00 pm
April 16, 2021 - 3:30 pm to 4:30 pm
April 21, 2021 - 12:00 pm to 1:00 pm