VECTOR | [3-0-0:3] |
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DESCRIPTION | This course covers the fundamentals of machine learning and artificial intelligence, and their applications in computer vision, image processing, natural language processing, and robotics. The topics include major learning paradigms (supervised learning, unsupervised learning and reinforcement learning), learning models (such as neural networks, Bayesian classification, clustering, kernels, feature extraction), and other problem solving techniques (such as heuristic search, constraint satisfaction solvers and knowledge-based systems) in AI. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6276) | Fr 01:30PM - 04:20PM | Rm 150, E1 | WU, Wenwei YUAN, Zixuan ZHANG, Weijia | 35 | 21 | 14 | 0 |
EXCLUSION | UFUG 1105 |
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DESCRIPTION | This is the first of a year-long sequence of two introductory courses in one-variable calculus, intended for first year undergraduate students. The emphasis is on the understanding of foundational concepts and practical skills in applying calculus, which are essential for their future study in various fields. Topics include approximation, continuity, limit, differentiation, high order approximations and differentiation, and applications to optimization, monotonicity, and convexity. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L02 (6300) | MoWe 09:00AM - 10:20AM | Rm 101, E1 | YUAN, Zixuan | 55 | 53 | 2 | 0 |