BROADER AND EARLIER ACCESS TO MACHINE LEARNING

4000.00

This poster presents the results of an ongoing project that has developed learning modules to provide access to the tools and techniques associated with machine learning to a broad category of undergraduate students. The changing nature of science and its reliance on massive data sets has led to the integral use of machine learning approaches in just about every discipline. Recognizing this shift, flexible teaching materials have been developed to provide educators and students in a wide variety of academic fields with relevant machine learning topics and discipline-ready activities. Goals, module design, example material, dissemination plans and evidence of student learning are presented.