This course introduces key machine learning techniques and their applications. The topics include overview of supervised learning, linear models, kernel methods, decision trees, neural networks, nearest neighbours, ensemble models, and unsupervised learning. Upon completion of this course, students should be able to apply various machine learning technique in develop intelligent data analysis systems.

CILO-1: An ability to analyse a problem, and identify and define the computing requirements appropriate to its solution. CILO-2: An ability to communicate effectively with a range of audiences. CILO-3: Recognition of the need for and an ability to engage in continuing professional development. CILO-4: An ability to use current techniques, skills and tools necessary for computing practice with an understanding of the limitations.