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| ATTRIBUTES | Common Core: Foundations (E-Comm) |
|---|---|
| PRE-REQUISITE | Gaokao English Language Score 130 or above or IELTS IELTS Band 6.0 overall with all sub scores at 6.0 or above" or IELTS Band 6.5 (overall) with some but not all subscores at or above 6.0 or HKDSE English Language Level 3 (overall) with all subscores at or above Level 3 or HKDSE English Language Level 4 (overall) or HKDSE English Language Level 5 (overall) with some but not all subscores at or above level 4 or equivalence of the above |
| EXCLUSION | UCUG 1050 |
| DESCRIPTION | This course aims for students in their first year of study and will develop students’ spoken and written language proficiency. The course also introduces academic literacy skills common to all disciplines. Students will learn to evaluate others’ opinions, develop strong arguments and communicate those arguments effectively in written and spoken English. In addition to traditional academic writing, the course includes elements of academic communication that go beyond the text level to incorporate academic communication that includes text and audio. They will also build skills and habits for self-directed learning at university. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| T13 (6283) | TuTh 01:30PM - 02:50PM | Rm 150, E1 | LI, Maosu | 26 | 26 | 0 | 0 |
| DESCRIPTION | Digital twins are transforming how we represent, understand, and manage cities, enabling new forms of analysis, automation, and decision support across building and urban scales. With the rapid growth of large-scale 3D information assets, e.g., meshes, point clouds, and semantic models, digital twin cities introduce critical challenges in information organization, integration, management, and scalable intelligence. This course focuses on 3D information technologies for digital twin cities, emphasizing how heterogeneous information from Building Information Modeling (BIM), City Information Modeling (CIM), and Internet of Things (IOT) are structured, integrated, and orchestrated within scalable data infrastructures and platforms. Students will explore the fundamental methods for organizing, managing, and interacting with large-scale urban information, including semantic representation, information integration, indexing, visualization, and real-time information management to support dynamic urban systems. Building on this foundation, the course introduces AI-driven urban applications, including machine learning, computer vision, and large language model agents, as new paradigms for interpreting, querying, and interacting with digital twins. By integrating information modeling, visualization, analytics, and AI, the course demonstrates how digital twins can support scalable intelligence and informed decision-making in real-world applications such as infrastructure management, urban planning, housing, and urban health. |
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| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6736) | Fr 03:00PM - 05:50PM | Rm 202, E1 | LI, Maosu | 15 | 15 | 0 | 0 |