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发布日期 :2022-03-17    阅读次数 :1616

University of Illinois Urbana-Champaign

Undergraduate Summer Online Course

July 2022 (具体开始时间待定)

Machine Learning (3 weeks)



Global Education and Training’s Telecommunication and Engineering Undergraduate Summer Online Course at the University of Illinois at Urbana Champaign offers students a foundational and forward-looking lectures in Machine Learning. Machine learning for Internet of Things (IoT) is central to the evolving IoT that is revolutionizing industry, personal lives,and virtual reality. Machine Learning for IoT innovations is making technology more accessible, secure, and smarter. Learn more about these emergent technologies from Illinois’ expert faculty, who will lead students in a live online classroom space. Illinois’ leading faculty will engage students in discussions on core mathematical principles, systems design, and real-world applications.Students are expected to participate in live discussions and problem solving during each live class session.


 Faculty Background

Professor Romit Roy Choudhury is a Jerry Sanders III AMD Scholar and Professor of ECE and CS at the University of Illinois at Urbana Champaign (UIUC). He joined UIUC from Fall 2013, prior to which he was an Associate Professor at Duke University. Professor Choudhury received his PhD in the CS department of UIUC in Fall 2006. His research interests are in wireless networking, mobile sensing, and applied signal processing. Along with his students, he received the following research awards, including the 2017 ACM MobiSys Best Paper Award, the 2016 Distinguished Alumni Award, the 2015 ACM Sigmobile Rockstar Award, the 2009 Hoffmann Krippner Award for Engineering Innovations, 2007 NSF CAREER Award, etc. Professor Choudhury was elected as an IEEE Fellow in 2019. For more information about Romit see


  3-Week Proposed Course Schedule

The course encompasses two components, 30 hours of online synchronous sessions, and 30 hours of offline learning sessions.

·     24 hours of online synchronous academic sessions, including faculty lectures, reading discussions, Q&A sessions, and a final assignment and evaluation. The faculty lectures include Machine learning for IoT Applications, Machine learning for IoT-- From Algorithms to Practice, as well as Machine Learning in Wireless, Mobile, and IoT Systems. The lectures are centered around Machine Learning for IoT with specific connections to applications like indoor localization, wearable computing, gesture recognition, Internet of acoustic things, and other modern technologies. Through the lectures, students will learn how algorithmic challenges can be handled, and how such algorithms need to be engineered and creatively applied,to bridge the gap between theory and practice.The teaching assistants will guide the students’ understanding of the topics by highlighting key points from the readings and answering students’ questions.

·     6 hours of online synchronous co-curricular sessions will diversify students’ learning experiences and outcomes. Students will attend guest speaker/panelist sessions with University of Illinois Ph.D. students and alumni. Topics may include applications and admissions process for graduate studies; writing a personal statement; conducting research as a doctoral student; keys to a successful engineering career; and more. The overall course will conclude with a learning outcome showcase and a course recognition ceremony led by University of Illinois staff.

·     30 hours of offline learning sessions: students are required to devote at least two hours every day to complete reading assignments, homework, group discussions, and a final assignment, which consists of at least 30 hours of offline learning sessions. Students will be assigned and receive reading materials during Orientation. Also, all students are required to complete these readings on their own during off line learning sessions, and then meet in live sessions with UIUC teaching assistants to prepare for faculty lectures. Guided by UIUC faculty, students are expected to complete a final assignment to apply knowledge learned from the course to solve problems in Machine Learning.


Online Course Format

The course will be conducted primarily as synchronous video conference meetings, with coursework assignments completed asynchronously. It is anticipated that video conference classes will be conducted using Zoom and using the University of Illinois' course management system. Course materials will be accessible to all participants one week before the starting of the course.  An orientation will be host by GET staff before the starting of the course.



3-Week Online Course Fee: $650.00 per person*,顺利完成项目后将获得pg电子试玩模式淳真国际交流奖学金全额资助。

Program fee includes tuition for development and instruction of online courses; assessment (grading) of participant performance in courses; online Learning Management System and videoconference system license; and university technology support fees.


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