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

Targeted Infusion Project: Development and Implementation of courses in Deep Learning for Industrial and Societal Applications
有针对性的注入项目:工业和社会应用深度学习课程的开发和实施
批准号:
2306300
负责人:
Abdelkrim Brania
金额:
$39.96万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2026-08-31

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中文摘要
翻译
历史上的黑人学院和大学本科生计划(HBCU-UP)通过有针对性的输液项目支持开发,实施和研究以证据为基础的创新模式和方法,以提高HBCU本科生的准备和成功,使他们可以追求科学,技术,工程或数学(STEM)研究生课程和/或职业。该项目的主要目标是为莫尔豪斯学院物理和社会科学专业的学生建立一个以深度学习为重点的数据科学课程序列。该项目的目标是:1)建立一个以深度学习中的涌现建模技术为重点的三门课程的数据科学序列,2)创造一个合作的内部培训机会,将课堂上获得的学术知识结合起来,并将其应用于实际的现实世界应用。数据科学课程序列将由两个学期的初级或高级学生课程和一个学期的合作内部实践培训机会组成。在两个学期的课程中,学生将学习机器学习和深度神经网络的基本原理。他们将学习使用典型的开源软件框架,如TensorFlow或PyTorch来解决指定的练习。将介绍客观检测和分割方面的简单实践项目。学生们将有机会使用Jetson Nano GPU来运行一辆类似玩具的自动驾驶汽车。一个学期的学期项目课程旨在让学生有机会与合作伙伴合作,解决真实的世界数据科学问题。通过知识传授和实践经验,将建立一个协同数据科学项目,帮助STEM领域历来代表性不足的学生应对社会现有劳动力的需求和挑战。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
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.
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