COURSE OBJECTIVES
The programme introduces participants to the latest technologies in artificial intelligence and machine learning. At the completion of this course, students will have the knowledge on the fundamentals of AI including the various types of machine learning algorithms. This course also aims to equip students with skills and hands-on experience in applying AI and ML on real-world data using the Internet-of-Things as an example application.
PROGRAMME HIGHLIGHTS
- Thematic discussions, live tutorials and short practice sessions from NUS faculty and teaching assistants.
- The live tutorials will cover hands-on exercises and in-depth discussions through interactive breakout rooms.
- The programme is designed with Continuous Assessments format to sharpen the understanding and application of ideas learned during the lectures.
- Mini Project – There will be a mini group project in which students will solve and analyse a problem related to AI and Machine Learning.
Who Should Attend
University students majoring in Science, Technology, Engineering, Computing, and Mathematics subjects.
Pre-Requisites
There are no specific pre-requisites in terms of math or computational science. However, familiarity with scientific programming languages such as Python would be helpful. The class will incorporate practical assignments in Python. Also, exposure to calculus, linear algebra, and statistics would be helpful.
Programme Schedule
For individuals interested in NUS SCALE Youth programmes, please
click here to enquire.
For schools/companies interested in customised and/or group bookings, please
click here.
Mode of Delivery
Blended Online Programme: 23 hours of hybrid online programme, including asynchronous lessons, tutorials and a final project presentation.
On-campus Programme: 15 hours of seminars, workshops, and a final project presentation.
Mode of Assessment
Students will be assessed via a variety of assignments and assessments:
- Individual assignments
- Group project
COURSE INSTRUCTORS
Below are the faculty members who have developed the course, and taught the programme in the past (names are arranged in alphabetical order):
Dr Mehul Motani, Associate Professor, Department of Electrical and Computer Engineering,
Faculty of Engineering
Prof Mehul Motani received the B.E. degree from Cooper Union, New York, NY, the M.S. degree from Syracuse University, Syracuse, NY, and the Ph.D. degree from Cornell University, Ithaca, NY, all in Electrical and Computer Engineering.
Prof Motani is currently an Associate Professor in the Electrical and Computer Engineering Department at the National University of Singapore (NUS) and a Visiting Research Collaborator at Princeton University, USA. He is also a member of the NUS Institute for Data Science, the N.1 Institute for Health, and the NUS Smart Systems Institute. Previously, he was a Visiting Fellow at Princeton University. He was also a Research Scientist at the Institute for Infocomm Research in Singapore, for three years, and a Systems Engineer at Lockheed Martin in Syracuse, NY for over four years. His research interests include information theory and coding, machine learning, biomedical informatics, wireless and sensor networks, and the Internet-of-Things.
Prof Motani was the recipient of the Intel Foundation Fellowship for his Ph.D. research, the NUS Annual Teaching Excellence Award, the NUS Faculty of Engineering Innovative Teaching Award, and the NUS Faculty of Engineering Teaching Honours List Award. He is a Fellow of the IEEE and has served as the Secretary of the IEEE Information Theory Society Board of Governors. He has served as an Associate Editor for both the IEEE Transactions on Information Theory and the IEEE Transactions on Communications. He has also served on the Organizing and Technical Program Committees of numerous IEEE and ACM conferences.
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CERTIFICATE OF COMPLETION
Successful participants who fulfill all program requirements, including meeting the minimum attendance and passing the assessment, will be awarded an e-Certificate of Completion and Assessment Report issued by NUS SCALE.
Certificate of Completion
A sample of the Certificate of Completion
Assessment Report
A sample of the Assessment Report.
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COMMENDATION LETTER
Participants from the project team with the highest score for the group project will also receive a commendation letter.
Commendation Letter
A sample of the Commendation Letter.
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SPEAK TO US
For enquiries, do contact us through following forms should you have any questions regarding this programme:
For individuals interested in NUS SCALE Youth programmes, please click here to enquire.
For schools/companies interested in customised and/or group bookings, please click here.
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