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+Data Science Events in October

+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. For more information, please visit our website at https://plus.datascience.duke.edu/

Upcoming In-Person Learning Experiences (IPLEs)

+DS will offer 7 In-Person Learning Experiences for October. These sessions offer the opportunity to dive deeper into topics and 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, October 1: Scaling to Big Data (David Carlson)

· Wednesday, October 9: Legal Levers for Innovation and Trustworthiness in Machine Learning (Arti Rai)

· Tuesday, October 15: Translating between Text and Images: Creative Applications with AttnGAN and Im2Text (Matthew Kenney) part of the Humanities/Social Sciences +DS track

· Wednesday, October 16: Neural Network Basics (Qiang Qiu)

· Monday, October 21: Convolutional Neural Networks for Image Analysis (Timothy Dunn)

· Tuesday, October 22, Machine Learning and Computer Vision for Neurodevelopmental Disorders: Helping One Child at a Time (Guillermo Sapiro)

· Wednesday, October 30, Biomedical Data Science and Machine Learning Applications in Healthcare (Jessilyn Dunn)

Anyone in the Duke community is welcome to join, there is no fee to attend, and no prior experience is necessary. Register for IPLEs on the +DS website: https://plus.datascience.duke.edu/learn-ds#iple

Upcoming Lunch and Learns

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. The sessions will be convenient for Duke medical professionals, located at the Trent-Semans Center Learning Hall.

A Window to the Brain: Analysis of Retinal Images with Deep Neural Networks

Tuesday, October 1 | 12:15 p.m. – 1:30 p.m. | Trent-Semans Center Learning Hall

Sharon Fekrat, MD, Professor of Ophthalmology; Associate Professor, Department of Surgery

Felipe Medeiros, MD, PhD, Joseph A.C. Wadsworth Professor of Ophthalmology

Dilraj Singh Grewal, MBBS, Associate Professor of Ophthalmology

Lawrence Carin, PhD, James L. Meriam Professor of Electrical and Computer Engineering; Vice President for Research, Duke University

Other upcoming events in this series:

  • Tuesday, November 5: Early Autism Screening with Machine Learning
  • Tuesday, December 3: Recommending MyChart Responses with Natural Language Processing

Lunch will be provided, anyone in the Duke community is welcome to join, and there is no fee to attend. To learn more, please visit: https://plus.datascience.duke.edu/learn-ds#lunch-and-learn

You can also watch the video from the September 24 lunch and learn on Digital Pathology: Identifying Thyroid Malignancy with Deep Learning.

New Reinforcement Learning Module Available in Coursera

A new module on Reinforcement Learning is now available in the +DS online learning modules. Reinforcement Learning is a fundamental concept in machine learning that is concerned with taking suitable actions to maximize rewards in a particular situation. After learning the initial steps of Reinforcement Learning, the module addresses Q Learning as well as Deep Q Learning, and discusses the difference between the concepts of Exploration and Exploitation and why they are important.

This new module is part of Duke’s “Introduction to Machine Learning” course in Coursera, which contains more than 50 videos plus readings, practice exercises, and learning comprehension quizzes. The content is organized into 5 modules and introduce the basics of data science across multiple important application domains. These online modules serve as a foundation for the in-person learning experiences and support a "flipped" learning experience for participants.

This Coursera curricula is available to all Duke students, trainees, faculty, and staff at no charge. To learn more, please visit: https://plus.datascience.duke.edu/learn-ds#online-modules

Photo: One of the 12 +DS student teams presenting their poster at our spring 2019 student showcase.