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Code Module Credits Duration Prerequisite(s)
Table III: Electives (Cont.)

COMP6148 Innovation and Technology in 3 45 hrs ---
Health and Wellness
This module aims to explore the latest innovations and technology applications in the
field of health, rehabilitation, and wellness. The module content covers digital health
technologies, wearable devices, health data analysis, telemedicine, personalized health
management and intelligent systems for health promotion. Students will learn how to
use these innovative technologies to improve the effectiveness of health management,
rehabilitation, and health care services and solve current challenges in the field of health
and wellness. Through theoretical learning and practical operations, students will master
the core skills of applying cutting-edge technologies in the field of health, rehabilitation
and wellness, laying a solid foundation for future innovation and research in related
fields.

COMP6149 Artificial Intelligence Assisted 3 45 hrs ---
Sports Performance Analysis
This module provides a comprehensive overview of how to process and interpret sports
performance data and predictions using data mining and machine learning techniques.
It introduces some theoretical aspects of game theory, probabilistic theory, and machine
learning, with the primary focus on practical applications in sports performance analysis
and sports decision-making. Topics include statistical and probabilistic methods for
analyzing sports performance data, game theory, data mining methods for extracting
insights from sports-related data, machine learning algorithms, neural networks, and
deep learning methods for complex data analysis, data extraction and common use cases
in performance analysis, data handling routines, validation methods and performance
measures, and visualization and analysis of results from sports performance data
analysis.
COMP6150 Selected Topics I 3 45 hrs ---
The selected topics are designed to accommodate new, advanced and state-of-the-art
technologies and to apply in sports that are not included in this curriculum. One example
is sports data mining. Data Mining is one of the most popular research fields in Computer
Science. The aim of this is to give an applicable understanding of the usage of data mining
as of decision making. In this module, several essential fields would be discussed,
including the classes of different algorithms and models, and the methodology of how
to choose a suitable algorithm. Classification, pattern recognition and different learning
types would be discussed and covered. Besides, other interdisciplinary topics, such as
mathematical and statistical modelling in sports analytics, can also be covered.
COMP6151 Selected Topics II 3 45 hrs ---
The selected topics are designed to accommodate new, advanced and state-of-the-art

technologies and to apply in sports that are not included in this curriculum. One example
is sports data mining. Data Mining is one of the most popular research fields in Computer
Science. The aim of this is to give an applicable understanding of the usage of data mining
as of decision making. In this module, several essential fields would be discussed,
including the classes of different algorithms and models, and the methodology of how
to choose a suitable algorithm. Classification, pattern recognition and different learning
types would be discussed and covered. Besides, other interdisciplinary topics, such as
mathematical and statistical modelling in sports analytics, can also be covered.
Remarks:
*In order to fulfill the graduation requirement, students must complete 30 credits, including 12 credits from
the compulsory modules listed in Table I, 9 credits from the Project Report in Table II ,and 9 credits from the
optional modules in Table III.

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