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DS

Your Field +DataScience

+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.

Learn +DS Online, then In-Person

+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.

Step One: Online Learning

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. 

Coursera at Duke modules

  • Module 1: Introduction to Machine Learning
  • Module 2: Basics Of Model Learning
  • Module 3: Image Analysis and Convolutional Neural Network
  • Module 4: Introduction to Natural Language Processing

Recorded Content from the Machine Learning Summer School

In addition to the aforementioned Coursera content, +DS offers recordings of Duke’s Machine Learning Summer School (MLSS), which was 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.

Step Two: In-Person Learning Experiences

Once you have reviewed the online content, +DS offers in-person 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.

Tuesday, November 27 - 4:00pm to 6:00pm
Instructor: Fan Li
Wednesday, November 28 - 4:00pm to 6:00pm
Instructor: Lawrence Carin
Monday, December 10 - 4:00pm to 6:00pm
Instructor: Ricardo Henao Giraldo