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9

135 hrs

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COMP6141 

This module provides students with core knowledge in the field of sports science and technology. The module content includes human anatomy and physiology, sports biomechanics, sports psychology, and sports nutrition. Students will learn how the human body systems collaborate during exercise, the effects of exercise on the body, and how to optimize athletic performance and prevent sports injuries using some of the latest technology. Through theoretical study and practical training, students will acquire basic skills in assessing athletic performance, designing training programs, and providing scientific guidance, laying a solid foundation for further research and application in the area of sports science and technology.

3

45 hrs

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COMP6142 

Recent advances in sports technologies have led to the rapid explosion of sports data. Sports data analytics derived from big data can help athletes and sports teams to better understand individual and team performances, improve team efficiency, and acquire competitive advantages. This learning module provides an overview of common big data applications and analytical techniques (e.g., statistics and probability, sentiment analysis, data visualization etc.) in sports and discusses some implementation issues related to sports data projects. As part of a group project, students will need to demonstrate the ability to come up with a plan based on a given sport-related case study and a relevant dataset. Students will acquire the knowledge and skills needed to effectively analyze and work with sports-related datasets.

3

45 hrs

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COMP6143 

Artificial Intelligence (AI) has become deeply integrated into our daily lives, often in ways we may not even realize. At the forefront of AI is Machine Learning (ML), a branch of AI that enables computers to learn and adapt without explicit programming. Over the past decade, ML has revolutionized sports industry with breakthroughs in sports technologies, sports prediction, and AI-assisted sports training. This module covers some of the key machine learning techniques, including decision tree, neural networks, deep learning, etc. The aim of the module is to equip students with both the theoretical foundation and practical skills to apply these methods across various domains, such as classification, regression, etc.

3

45 hrs

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COMP6144 

This module introduces the latest developments and applications in the field of sports technology. The module content covers topics such as motion sensors, wearable devices, virtual reality and augmented reality technologies, sports data analysis, and biomechanical measurement tools. Students will learn how to utilize these technologies to monitor and enhance athletes' performance, improve training methodologies, as well as to help athletes prevent and treat sports injuries. In addition, students will explore ethics and regulations concerning the use of sports technologies. Through theoretical study and practical application, students will acquire the core skills needed to assess and apply sports technologies. This module will prepare students for innovation and technological development in the fields of sports science and coaching.

3

45 hrs

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COMP6298 

Students are required to apply the techniques and technologies which they have learned in a significant advanced project. Under the supervision of an advisor, the students shall focus on a contemporary research topic or technological problem and make use of the leading-edge techniques to produce new research findings or solutions. Upon completion, the Project Report is to be submitted and evaluated using the standard criteria for advanced project.

9

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COMP6145

This module explores the latest applications and research advancements of intelligent sports technology in rehabilitation therapy. Topics include AI applications in rehabilitation, wearable devices, intelligent rehabilitation systems, virtual reality, and robot-assisted rehabilitation. Students will learn to design and implement personalized rehabilitation programs to enhance therapeutic outcomes and patient experiences.

3

45 hrs

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COMP6146

This module introduces the latest sports rehabilitation methods and tools. It covers physical therapy techniques, exercise therapy, manual therapy, use of rehabilitation equipment, and advanced assessment tools such as motion capture systems and biomechanical analysis devices. Students will learn to prevent, diagnose, and treat sports injuries, create personalized rehabilitation plans, and evaluate rehabilitation outcomes.

3

45 hrs

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COMP6147

This module covers the application of intelligent technology in the field of sports rehabilitation. Students will learn about smart sensors, motion tracking technology, and intelligent assistive devices, focusing on their principles and methods in rehabilitation sports. The module includes the design and development of intelligent rehabilitation equipment, biomechanical analysis, and the design of exercise evaluation and training programs. Through theoretical lectures and practical exercises, students will master the basic principles and operational skills of intelligent rehabilitation sports engineering to enhance the effectiveness and efficiency of rehabilitation exercises.

3

45 hrs

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COMP6148

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.

3

45 hrs

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COMP6149

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.

3

45 hrs

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COMP6150

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.

3

45 hrs

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COMP6151

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.

3

45 hrs

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