Year of Study:	4
Credit Units:	3
Duration:	45hours
Prerequisites:	AMS2002 and AMS3640 except with the permission of the Module Coordinator or With the Instructor’s permission and upon endorsement of the relevant Head or Programme Director.

Deep learning has been widely applied to solve various real-world machine learning problems, such as image recognition problems, speech recognition problems, text mining problems, etc. In this module, students will learn the most common types of neural networks and deep learning methodologies on both theory and practice. Students will apply deep learning methodologies to solve real-life problems in application domain(s) such as imaging problems. 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 of the most common types of neural networks and deep learning methodologies;


2. acquire the basic knowledge of application domain(s) of deep learning methodologies;


3. apply neural networks and deep learning methodologies to practical problems; and


4. interpret and present the results in a scientific and concise manner; and work effectively in a