Targeted Infusion Project: Development and Implementation of courses in Deep Learning for Industrial and Societal Applications

Morehouse College, Atlanta GA

Investigators

Abstract

The Historically Black Colleges and Universities Undergraduate Program (HBCU-UP) through Targeted Infusion Projects supports the development, implementation, and study of evidence-based, innovative models and approaches for improving the preparation and success of HBCU undergraduate students so that they may pursue science, technology, engineering, or mathematics (STEM) graduate programs and/or careers. The primary objective of this project is to establish a data science course sequence focusing on deep learning for students majoring in physical and social sciences at Morehouse College. This project goals are to 1) establish a three-course data science sequence focusing on emergent modeling techniques in deep learning, and 2) create a collaborative in-house training opportunity to bring together the academic knowledge gained in the classroom and apply it to practical real-world applications. The data science course sequence will be composed of a two-semester course for junior or senior students and a one-term collaborative in-house hands-on training opportunity. In the two-semester course, the students will learn the fundamental principles of machine learning and deep neural network. They will learn to use typical open-source software frameworks such TensorFlow or PyTorch to solve the assigned exercises. Simple hands-on projects in objective detection and segmentation will be introduced. The students will have the opportunity to use a Jetson Nano GPU to run an autonomous toy-like vehicle. The one semester term project course aims to give the students the opportunity to team up with the collaborative partners to work on real world data science problems. A synergy data science project will be established via knowledge delivery and practical experiences that prepares students historically underrepresented in STEM for the demands and challenges of the existing workforce in the society. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.