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| DESCRIPTION | This course provides guidance to undergraduate students of the AI major for their academic path and future. This course is mostly introductory and aims to inspire UG students for their academic path development and growth of maturity during their UG study. Activities may include seminars, workshops, advising and sharing sessions, interaction with faculty and teaching staff, and discussion with student peers or alumni. Graded P or F. |
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| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6417) | Mo 04:30PM - 05:20PM | Rm 101, W1 | BAI, Ge CHEN, Huangxun CHU, Xiaowen KAN, Ge Lin LIANG, Junwei QIN, Chengwei RIKOS, APOSTOLOS WANG, Xin WANG, Zeyu XIE, Sihong XIE, Zeke YANG, Menglin YUE, Yutao | 100 | 55 | 45 | 0 | The class will be delivered by the following instructors and contents as below: W1: Zeke XIE - Overview of Deep Learning Theory W2: Yutao YUE - Towards Conscious AI W3: Menglin YANG - Foundation of LLM: From Pretraining, Mid Training to Post Training W4: Xiaowen CHU - Magic of Low-Precision Computing behind LLMs W5: Sihong XIE - Interpretable AI W6: Xin WANG - Foundations of Quantum Computing W7: Ge BAI - Quantum Entanglement and Applications W8: Chengwei Qin - LLM Reasoning and Agent W9: Zeyu WANG - Toward Synergistic Human-AI Content Creation W10: Huangxun CHEN - Overview of Embedded AI W11: Ge Lin Kan - Generative AI for Urban Digital Twin W12: Junwei Liang - Towards General Service Embodied AI W13: Apostolos RIKOS - AI and Multi-Agent Networks |
| PRE-REQUISITE | UFUG 2601 OR UFUG 2602 |
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| EXCLUSION | DSAA 3051 |
| CROSS CAMPUS COURSE EQUIVALENCE | COMP 4221 |
| DESCRIPTION | This course provides a comprehensive journey into Natural Language Processing, first establishing the essential computational fundamentals of words, syntax, and semantics, and then advancing to the modern architectures that define the LLM era, such as transformers and GPT. You will learn to bridge classic techniques with cutting-edge applications—mastering pre-training, fine-tuning, and prompt engineering—while critically examining the advanced capabilities and profound responsibilities surrounding fairness, security, and interpretability. Through a blend of foundational theory and hands-on projects, this course equips you to build, innovate, and lead in the rapidly evolving field of applied NLP. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6428) | MoWe 12:00PM - 01:20PM | Rm 101, E1 | XIE, Sihong | 80 | 80 | 0 | 0 |