ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (COMPUTER VISION)
Machine Learning (ML), a branch of Artificial Intelligence, has proven useful in many fields, such as medical diagnosis, e-commerce, security, education, and so on. This short course introduces the basic technical concepts in ML, especially where it is used in image processing. You will learn enough to implement a simple system that recognizes traffic signs, and be able to further your own in-depth study into this exciting field.
| Welcome message from Dean of NUS SCALE
||Tutorials conducted over Zoom
Knowledge of: Single-variable Calculus, Matrix and Vectors, Probability and Statistics. Prior programming experience in a modern language, eg. Java, Python, C#, C/C++.
WHO SHOULD ATTEND
Undergraduates with programming experience and are interested in exploring machine learning.
MODE OF DELIVERY
23 hours of hybrid online programme, including asynchronous lessons, tutorials and a final project presentation.
MODE OF ASSESSMENT
- Continuous Assessment: Quiz
- Group project: Traffic Sign Recognition
Dr Terence Sim, Associate Professor, NUS School of Computing
Prof Terence Sim is an award-winning teacher and researcher with over 20 years of experience at the NUS School of Computing. His research areas include: computer vision, biometrics, and machine learning. He serves as Editor-in-Chief of the International Journal of Pattern Recognition and Artificial Intelligence. Prof. Sim obtained his PhD from Carnegie Mellon University, MSc from Stanford University, and SB from the Massachusetts Institute of Technology.
CERTIFICATE OF COMPLETION
Successful participants who complete all requirements of the programme including passing the assessment will receive a certificate of completion issued by NUS SCALE.
A sample of the certificate of completion can be found here:
Participants from the project team with the highest score for the group project will also receive a commendation letter. A sample is shown below:
7 January to 12 February 2023
in collaboration with Looker Education Group