Year of Study:	3-4
Credit Units:	3
Duration:	45hours
Prerequisites:	AMS2002 except with the permission of the Module Coordinator or With the Instructor’s permission and upon endorsement of the relevant Head or Programme Director.

This module introduces students the basic concepts, developments and applications of AI and cloud computing that are related to machine learning. Their impacts/implication on society will also be discussed. In addition, it provides students with the machine learning methodologies and algorithms that automate analytical model building for solving real-life problems. Topics selected include supervised learning, unsupervised learning, ensemble learning, kernel methods, module evaluation and advanced topics in machine learning. Students are also required to work effectively in a team to complete a project.

Upon completion of this module, students should be able to:

1. understand the basic concepts, development, applications and social impact of AI and cloud computing, and examine the importance of machine learning methodologies and algorithms;


2. apply supervised and unsupervised learning methodologies;


3. examine the strengths and weaknesses and evaluate the effectiveness of supervised and unsupervised learning algorithms; and


4. interpret and present the results in a scientific and concise manner; and work effectively in a team and solve real-life problems.