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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 (6363) | 01-SEP-2025 - 05-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | DAI, Enyan | 155 | 151 | 4 | 0 | The class will be delivered by the following instructors as below. W1-Enyan Dai W2-Bingzhuo Zhong W3-Xin Wang W4-Sihong Xie W5-Menglin Yang W6-Yingcong Chen W7-Junwei Liang W8-Changhao Chen W9-Zeke Xie W10-Yutao Yue W11-Li LIU W12-Xuming Hu W13-Apostolos Rikos |
| 08-SEP-2025 - 12-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | ZHONG, Bingzhuo | ||||||
| 15-SEP-2025 - 19-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | WANG, Xin | ||||||
| 22-SEP-2025 - 26-SEP-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | XIE, Sihong | ||||||
| 29-SEP-2025 - 11-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | YANG, Menglin | ||||||
| 13-OCT-2025 - 17-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | CHEN, Yingcong | ||||||
| 20-OCT-2025 - 24-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | LIANG, Junwei | ||||||
| 27-OCT-2025 - 31-OCT-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | CHEN, Changhao | ||||||
| 03-NOV-2025 - 07-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | XIE, Zeke | ||||||
| 10-NOV-2025 - 14-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | YUE, Yutao | ||||||
| 17-NOV-2025 - 21-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | LIU, Li | ||||||
| 24-NOV-2025 - 28-NOV-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | HU, Xuming | ||||||
| 01-DEC-2025 - 05-DEC-2025 Tu 09:00AM - 09:50AM | Lecture Hall B | RIKOS, APOSTOLOS |
| PRE-REQUISITE | UFUG1103 AND UFUG2104 |
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| DESCRIPTION | This course introduces the fundamentals of embodied AI. Students will explore key principles and algorithms to build modern autonomous embodied AI systems. Key topics include machine perception, planning and decision-making algorithms. Through this course, students will learn and practice the foundational principles, techniques, and tools to build new embodied autonomous AI systems. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L02 (6680) | We 01:30PM - 04:20PM | Rm 149, E1 | CHEN, Changhao | 50 | 14 | 36 | 0 |
| VECTOR | [3-0-0:3] |
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| DESCRIPTION | Navigation is a core capability for intelligent vehicles, enabling environment perception, localization, and decision-making. This course provides a comprehensive understanding of vision-based navigation for unmanned systems, focusing on mobile robots and self-driving vehicles. It covers a wide range of topics, including multiview geometry, visual/-inertial state estimation, simultaneous localization and mapping (SLAM), place recognition, scene perception, and recent advances in embodied AI, equipping students with the theoretical and practical skills to design advanced navigation systems. Through hands-on projects using real-world datasets, students will gain experience in implementing and evaluating visual navigation solutions. Ideal for those interested in intelligent systems, computer vision, and AI, this course bridges theory and practice for autonomous systems development. |
| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6159) | Tu 01:30PM - 04:20PM | Maker Space W1-621K | CHEN, Changhao | 30 | 17 | 13 | 0 |