Handbook

This course will expose cyber security, decision analytics, space, project management, and systems engineering students to the experience of when and how to apply machine learning to solve different real-life problems. The students will master concepts such as learning from data, feature selection, regression, classification, clustering, and modes of learning such as supervised vs. unsupervised learning and biases in machine learning. They will also be exposed to the similarities and differences when applying machine learning to different modalities, such as time series data, image processing, and text analytics. This course will be a hands-on course with a low to moderate technical level that suits students who are interested in applying machine learning. The students will be able to design AI solutions that utilise existing machine learning algorithms to solve real-life problems, and then evaluate the performance of these systems and analyse the potential of recommending these systems to the decision makers.