University of Hong Kong

This course is inquiry-based, interactive, and hands-on, focusing on how to design effective, human centered generative artificial intelligence (GenAI) applications in business contexts. It is suitable for undergraduate students with no technical background. The course builds AI literacy through simulation games developed by the instructor. The core of the course guides students through real-world applications of GenAI across text, code, image, audio, and video. Students gain practical experience using GenAI tools and applying them to solve business problems. The course includes critical discussions on the implications of GenAI, covering issues such as privacy, algorithmic bias, labor impact, job displacement, and ethical design. It helps students consider not only what GenAI can do, but what it should do. From a career perspective, the course equips students to act as effective consultants for AI applications, organizational change, leadership, digital transformation, and sustainability. 

Film-making and TV production are becoming increasingly international, rendering translation almost indispensable to the industry. Translating films and TV shows for dubbing and subtitling requires specialized skills distinct from those used in other fields. This course focuses on such skills, with an emphasis on audio-visual awareness and cinematic elements such as drama, dialogue, vernacular, and pacing. Critical theories on media and on cultural production and consumption are introduced. Students learn through hands-on translation of feature films and TV programs, as well as critiques of film and TV translations.

This course cultivates the fundamental literacy skills required for commercial music composition. The topics covered include pop songwriting, beat making, film scoring, and jingle production. Students are introduced to contemporary practices in the music industry through music demos, instrumental tracking, music arrangement, and music production techniques.

This course introduces the mathematical, statistical, and computational challenges in natural language processing. It covers the main applications of NLP techniques and a range of models in structured prediction and deep learning. Students gain a thorough introduction to cutting-edge machine learning and deep learning techniques for NLP. This course covers a broad range of topics including text classification, sentiment analysis, neural network, word embedding, sequence models, language models, machine translation, topic detection, and ChatGPT. The underlying techniques from probability, statistics, machine learning, transformer and deep learning are also introduced. Prerequisites: Pass in STAT2602 and COMP2119 or same level. Proficiency in Python.

This course is unique as it is co-organized by three faculties: Engineering, Medicine, and Science. This interdisciplinary collaboration highlights the importance of “biomimicry” and nature-inspired technologies that go beyond traditional disciplinary boundaries. Students in this course benefit from a comprehensive and diverse range of knowledge, merging insights from engineering, medicine, and science. By exploring how nature inspires technological advancements, students gain interdisciplinary skills and a broader perspective. The course is structured around three themes: industrial technology, biomedical technology, and environmental technology. Throughout this course, students learn to develop innovative ideas rooted in biomimicry to address real-world problems. Working in cross-faculty groups, students collaborate to design and build solutions that leverage the principles of biomimicry. This course equips students with the tools to contribute to sustainable and innovative technologies, preparing them for the challenges of the modern world.

This course uses an application-oriented approach to introduce students to the core concepts of psychometrics, a rigorous, scientific discipline of psychological testing and measurement. Students are provided with hands-on experiences to apply statistical methods for constructing and developing psychological measurement scales empirically as well as introductory exposure to instruments used by psychologists to assess intelligence, personality, and occupationally relevant attributes. Topics covered include: the context of testing and measurement; the testing process; test standardization; reliability and validity; intelligence and its appraisal; personality assessment; special domain testing; occupational applications; large-scale measurements; ethics and prospects.

This course looks at the relationship between the built environment and spiritual space with special focus on Southeast Asia. It looks at a range of spiritual practices and the forms they take including temples, mosques, shrines, and symbols. It addresses how religion shapes and connects cities in different ways as well as how globalization transforms and is transformed by spiritual space. The course examines debates surrounding these questions through cases within and beyond Southeast Asia. Topics range from ghost films to heritage sites. It provides a strong understanding of the religious and spiritual practices, global processes and political events shaping Southeast Asia. It also develops visual analysis skills necessary to read and write about spiritual space in a variety of forms. Course discussions and assignments unpack the aesthetic traditions, politics, and morals surrounding specific cases in order to complicate what it means to be global, regional or local. The content goes beyond Southeast Asia and cuts across disciplines, drawing from Art and Architectural History, Anthropology, Urban Planning, and Geography.

This course critically examines the issue of endangered languages, focusing on the impacts of globalization, ethnic identity, and language policies on language survival. It explores historical and contemporary factors, including population movements, war, trade, and colonization, that have shaped linguistic diversity. The course investigates why a small number of global languages dominate while thousands of minor languages face decline, and considers debates around language preservation, revitalization, and the pressures of modernity. Students analyze the political, cultural, and educational forces that influence language use and endangerment, developing insight into the tension between preserving linguistic heritage and adapting to a globalized world.

This course introduces the basic theories, model architectures, algorithms, and implementation of deep learning for computer vision. Students obtain hands-on experience on implementing and training deep neural networks for computer vision tasks. The course covers the following topics: (1) neural network optimization algorithms; (2) backbone network architectures for computer vision, including convolutional neural networks and transformers; (3) network structure design for visual recognition tasks (image classification, object detection, image segmentation), and visual content generation tasks; (4) implementation and training of neural networks for computer vision tasks; (5) advanced topics in computer vision and deep learning. 

The course covers advanced topics and techniques in big data, with a focus on the algorithmic and system aspects. It provides both theoretical and hands-on experience in big data and data mining. Topics include MapReduce, textual data management, graph data management, uncertain data management, association rule mining, and state-of-the-art data mining techniques. It also covers recent developments and progress in selected areas.