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  1. The course is designed for those who want to acquire the knowledge of deep learning and build their own AI applications using AI platforms and API. Prerequisites : To get the most out of the course, participants are expected to have some basic knowledge in Android app or Java programming.

    • Knowledge Engineering and Computational Creativity
    • Big Data and Infrastructure
    • Machine Learning
    • Statistical Modelling & Data Mining
    • Deep Learning and Its Application
    • Autonomic Computing and Robotics
    • Masters Project
    Introduce the concept of knowledge engineering, the state-of-the-art, and application scenarios;
    Develop an understanding of the key concepts of knowledge engineering, including the tools and approaches;
    Provide practical experience with state-of-the-art tools and libraries to build knowledge-based applications;
    Promote the development of investigative and independent research and development skills.

    This module aims to understand the selection criteria and use cases related to each class of database system.

    To introduce the theory underpinning core algorithms and concepts in machine learning;
    To provide the practical programming skills required to perform supervised and unsupervised machine learning on real data-sets;
    To introduce students to areas of recent research in machine learning, such as probabilistic programming and explainable AI.

    Automated data collection tools lead to large amounts of data stored in databases, data warehouses and other information repositories. Automated data analytics and mining techniques are becoming essential components to any information system. The aim of this module is to equip students with a systematic understanding of knowledge of the underlying ...

    Deep learning is an emerging and important focus area of Artificial Intelligence (AI). It aims to learn models and patterns as in conventional machine learning approaches, but it has the ability to discover more accurate representations without manual intervention for new types of domains. More recent advances on deep learning have led to very succ...

    Develop expertise in autonomic/self-managing (self*) system concepts;
    Provide expertise in how autonomicity may be designed into new and retrofitted into existing systems including using an agent based approach;
    Explore practically coding AI & self* principles for Robotics
    Stimulate interest in emerging Autonomic Computing & Robotics research that affects next generation AI & computation paradigms.

    The research project offers the student an opportunity to complete a scholarly yet realistic piece of work during which material developed throughout the course and extended through in-depth literature research can be related and applied to a problem drawn from a research area. The project tests the inventiveness, the critical capacities, the proje...

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  3. The Master of Science in Artificial Intelligence [MSc(AI)] programme provides students with foundational principles and knowledge in AI, and develops their practical skills and capabilities in applying AI to solve real world problems with ethical awareness.

  4. It is the 1 st Bachelor of Engineering programme in Artificial Intelligence (AI) in Hong Kong. Artificial Intelligence (AI) is an emerging engineering discipline that focuses on the technological innovations in enabling computing systems to behave and discover new knowledge with human-like intelligence.

  5. The core courses of the MSc(AI) programme will enable students to delve into the fundamental concepts, methodologies in artificial intelligence and the underlying mathematical and statistical tools with an effort to equip them with a solid foundation in both theory

  6. Relevant Programmes. MSc Internet of Things Postgraduate Diploma in Information Technology. The programme aims to prepare students for an industrial career, with skills in the fields of computing, knowledge presentation, reasoning, autonomic computing, robotics,...