XU, Chen - HKUST Class Schedule & Quota

Class Schedule & Quota
2026-27 Fall 2025-26 Summer 2025-26 Spring 2025-26 Winter
2026-27 Fall
Common Core Course
The class information on this page will normally be updated every 15 to 20 minutes during class enrollment period.
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This service was first adapted from a student contribution in 2011-12 Fall. The efforts of all concerned are duly acknowledged.

AIAA AMAT BSBE CMAA CNCC CNGF DLED DSAA EOAS FTEC FUNH INFH INTR IOTA IPEN LANG MICS MSSM PDEV PLED ROAS SEEN SMMG SOCH SYSH UCMP UCUG UFUG UGOD

COURSE INFO

PRE-REQUISITE	UFUG 2601 OR UFUG 2602
DESCRIPTION	The objective of this course is to present an overview of the principles and practices of AI and to address complex real-world problems. Through introduction of AI tools and techniques, the course helps students develop a basic understanding of problem solving, search, theorem proving, knowledge representation, reasoning and planning methods of AI; and develop practical applications in vision, language, and so on. Topics include foundations (search, knowledge representation, machine learning and natural language understanding) and applications (data mining, decision support systems, adaptive web sites, web log analysis).

PRE-REQUISITE

UFUG 2601 OR UFUG 2602

DESCRIPTION

The objective of this course is to present an overview of the principles and practices of AI and to address complex real-world problems. Through introduction of AI tools and techniques, the course helps students develop a basic understanding of problem solving, search, theorem proving, knowledge representation, reasoning and planning methods of AI; and develop practical applications in vision, language, and so on. Topics include foundations (search, knowledge representation, machine learning and natural language understanding) and applications (data mining, decision support systems, adaptive web sites, web log analysis).

AIAA 2205 - Introduction to Artificial Intelligence (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L02 (6931)	MoWe 10:30AM - 11:50AM	Lecture Hall A	XU, Chen	100 Quota/Enrol/Avail For UG year 2 & above students: 100/0/100	0	100	0

COURSE INFO

PRE-REQUISITE	UFUG 2601 OR UFUG 2602
DESCRIPTION	This undergraduate course provides a solid foundation in Python programming tailored for artificial intelligence applications. It begins with core Python concepts, including data types, control flow, functions, and object-oriented programming. Students then explore machine learning essentials using NumPy, Matplotlib, and scikit-learn for scientific computing, visualization, and implementing basic supervised and unsupervised models. The course further introduces deep learning with PyTorch, covering neural networks, optimization, transformers, large language models (LLMs), and AI agents. A distinctive module focuses on programming with AI, examining AI coding copilots, their workflows, practical strengths and limitations, and how to collaborate effectively with these tools. The course concludes with a final capstone project in which students design, implement, and present a substantial AI application, demonstrating their ability to apply Python both to build AI systems and to leverage AI tools in modern development.

PRE-REQUISITE

UFUG 2601 OR UFUG 2602

DESCRIPTION

This undergraduate course provides a solid foundation in Python programming tailored for artificial intelligence applications. It begins with core Python concepts, including data types, control flow, functions, and object-oriented programming. Students then explore machine learning essentials using NumPy, Matplotlib, and scikit-learn for scientific computing, visualization, and implementing basic supervised and unsupervised models. The course further introduces deep learning with PyTorch, covering neural networks, optimization, transformers, large language models (LLMs), and AI agents. A distinctive module focuses on programming with AI, examining AI coding copilots, their workflows, practical strengths and limitations, and how to collaborate effectively with these tools. The course concludes with a final capstone project in which students design, implement, and present a substantial AI application, demonstrating their ability to apply Python both to build AI systems and to leverage AI tools in modern development.

AIAA 3102 - Python Programming with Artificial Intelligence (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L02 (6555)	We 01:30PM - 02:50PM	Rm 102, W4	XU, Chen	96 Quota/Enrol/Avail UG Year 3&4 AI students: 96/0/96	0	96	0
L02 (6555)	Fr 01:30PM - 02:50PM	Rm 102, W4	TBA	96 Quota/Enrol/Avail UG Year 3&4 AI students: 96/0/96	0	96	0