Course Description

Overview
Artificial intelligence (AI) in biomedical research has grown exponentially in the past decade. AI can be used to uncover powerful new insights in data that your lab is already collecting. This workshop has two primary components.

First, participants will engage in discussions that cover recent advances in artificial intelligence (AI) and how these developments can be used in biomedical research. Topics will include active learning, adversarial learning, Bayesian deep learning, reinforcement learning, semi-supervised learning, self-supervised learning, and transfer learning. These topics will be covered in an integrated manner: the discussions will explore how different facets of AI can interact with each other to generate high-quality results.

Second, participants will work with the instructor to design and implement AI project(s). These projects will have direct relevance to the research being done by each participant. This workshop will have 1 day of discussion followed by 1 week of offline work where the participants communicate directly with the instructors about project development.

Who Should Attend
Postdocs, staff scientists, principal investigators, and institute/center leadership   

Prerequisite
Basic computing skills

Credit
Although no grades are given for courses, each participant will receive Continuing Education Units (CEUs) based on the number of contact hours.   One CEU is equal to ten contact hours. Upon completion of the course each participant will receive a certificate, showing completion of the workshop and 2.1 CEUs.

This workshop applies toward the Bioinformatics Endeavor digital badge.

Notification

• All cancellations must be received in writing via email to Ms. Carline Coote at registrar@faes.org.
• Cancellations received after 4:00 pm (ET) on business days or received on non-business days are time marked for the following business day.
• All refund payments will be processed by the start of the initial workshop.