 |
| PRE-REQUISITE | (UFUG 2102 OR UFUG 2103) AND AIAA 2711 |
|---|---|
| DESCRIPTION | Quantum computing represents a revolutionary computing paradigm with transformative potential for next-generation AI. This course provides a comprehensive introduction to quantum computing and quantum AI, guiding students from foundational concepts—such as qubits and quantum circuits—to advanced topics, including quantum algorithms, quantum error correction, quantum simulation, and quantum programming. The curriculum also introduces the foundations of the emerging area of quantum AI, covering quantum neural networks, quantum machine learning methods, and AI applications in quantum computing. It spans material from basic principles to the latest cutting-edge developments. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6553) | MoWe 12:00PM - 01:20PM | Rm 101, E4 | BAI, Ge WANG, Xin | 40 Quota/Enrol/Avail UG Year 3&4 AI students: 40/0/40 | 0 | 40 | 0 |
| PRE-REQUISITE | DSAA 2011 |
|---|---|
| DESCRIPTION | Learning and optimization serve as the foundational block for many artificial intelligence algorithms. Our initial focus is on convex analysis and on modeling problems as convex problems, while later on in the course we will shift the focus to different algorithms for convex optimization and nonconvex optimization. The techniques introduced in this course will be motivated by needs of problems and applications in Machine Learning and Deep Learning. The topics range from foundational material to cutting-edge trends. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6559) | Mo 01:30PM - 02:50PM | Rm 102, E1 | GONG, Zijun WANG, Xin | 40 Quota/Enrol/Avail UG Year 3&4 AI students: 40/0/40 | 0 | 40 | 0 | |
| Fr 09:00AM - 10:20AM | Rm 102, E1 | GONG, Zijun WANG, Xin |
| DESCRIPTION | This inquiry-based course aims to introduce students to the concepts and skills needed to drive digital transformation in the information age. Students will learn to conduct research, explore real-world applications, and discuss grand challenges in the four thrust areas of the Information hub, namely Artificial Intelligence, Data Science and Analytics, Internet of Things, and Computational Media and Arts. The course incorporates various teaching and learning formats including lectures, seminars, online courses, group discussions, and a term project. |
|---|
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6771) | Tu 09:00AM - 10:50AM | Lecture Hall B | LI, Hongyu TANG, Nan WANG, Xin WANG, Yuyang | 200 Quota/Enrol/Avail PhD(INFH): 90/0/90 | 0 | 200 | 0 | |
| L02 (6772) | We 01:30PM - 03:20PM | Lecture Hall B | LI, Hongyu TANG, Nan WANG, Xin WANG, Yuyang | 200 Quota/Enrol/Avail PhD(INFH): 90/0/90 | 0 | 200 | 0 |
| ATTRIBUTES | Comon Core: Broadening (Social Analysis) |
|---|---|
| EXCLUSION | UFUG 1801 |
| CROSS CAMPUS COURSE EQUIVALENCE | ECON 1220 |
| DESCRIPTION | Students learn the "economic way of thinking" in this course. We will explore fundamental microeconomic concepts and tools such as comparative advantage and specialization, demand-supply analysis, market equilibrium, government's role in markets, game theory, and people's interactions in order to explain and analyze consumer and producer decisions and social issues. Students will develop problem-solving abilities in dealing with new social issues as well as develop their sense of community and consideration through the lens of microeconomics. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L03 (6333) | We 12:00PM - 02:20PM | Rm 202, E3 | WANG, Xin | 40 | 0 | 40 | 0 | |
| T03 (6336) | Th 04:30PM - 05:20PM | Rm 150, E1 | WANG, Xin | 40 | 0 | 40 | 0 |
| EXCLUSION | UFUG 2102 |
|---|---|
| DESCRIPTION | Linear algebra is central to almost all areas of mathematics and is also used in most sciences and fields of engineering. This course provides a comprehensive introduction to topics of linear algebra studies, including linear systems, vector spaces, matrices, linear mappings and matrix forms, inner products, orthogonality and Gram-Schmidt process, eigenvalues and eigenvectors, symmetric matrices and diagonalization, and determinants. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6807) | Fr 03:00PM - 05:50PM | Rm 101, E4 | LIU, Jinguo WANG, Xin | 48 | 0 | 48 | 0 | > Experimental Class |
| T01 (6817) | Mo 06:30PM - 07:20PM | Rm 101, E4 | LIU, Jinguo WANG, Xin | 48 | 0 | 48 | 0 |