ZHANG, Chao - HKUST Class Schedule & Quota

Class Schedule & Quota
2025-26 Spring 2025-26 Winter 2025-26 Fall 2024-25 Summer
2025-26 Spring
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.

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COURSE INFO

DESCRIPTION	This is the compulsory one-year development course for FTEC students. The course provides academic and professional advising to students on the development of professional ethics, social awareness, responsibilities, and communication skills. An intended learning outcome is to develop a holistic, interdisciplinary, and evidence-based understanding of the issues in FinTech in the financial markets. Grading Type: Pass/ Fail

DESCRIPTION

This is the compulsory one-year development course for FTEC students. The course provides academic and professional advising to students on the development of professional ethics, social awareness, responsibilities, and communication skills. An intended learning outcome is to develop a holistic, interdisciplinary, and evidence-based understanding of the issues in FinTech in the financial markets. Grading Type: Pass/ Fail

FTEC 1010 - Academic Orientation for FTEC Students (1 unit)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6409)	We 05:00PM - 05:50PM	Rm 101, E1	BAI, Ruoqi CAI, Ning CAO, Yiyue LI, Siguang QIU, Shi SUN, Shuo WANG, Junxuan WANG, Xuechao YUAN, Zixuan ZHANG, Chao ZHANG, Guang ZHANG, Leifu ZHANG, Liang ZHANG, Yi ZHU, Zimu	60	56	4	0

COURSE INFO

VECTOR	[3-0-0:3]
DESCRIPTION	This course offers an in-depth introduction to the fundamental concepts of artificial intelligence (AI) and its advanced applications in finance. It covers key AI techniques, including linear models, tree-based methods, clustering algorithms, neural networks, and reinforcement learning, with an emphasis on both theoretical and practical implementation. Applications in finance, including risk management, asset pricing, fraud detection, and high-frequency trading, will be critically analyzed through real-world datasets. The course fosters a deep understanding of AI methods, enabling students to engage in independent research, and contribute to the development of novel financial technologies.

VECTOR

[3-0-0:3]

DESCRIPTION

This course offers an in-depth introduction to the fundamental concepts of artificial intelligence (AI) and its advanced applications in finance. It covers key AI techniques, including linear models, tree-based methods, clustering algorithms, neural networks, and reinforcement learning, with an emphasis on both theoretical and practical implementation. Applications in finance, including risk management, asset pricing, fraud detection, and high-frequency trading, will be critically analyzed through real-world datasets. The course fosters a deep understanding of AI methods, enabling students to engage in independent research, and contribute to the development of novel financial technologies.

FTEC 6910F - Machine Learning for Finance (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6746)	Tu 09:00AM - 11:50AM	Rm 202, E4	CHEN, Zhanghao ZHANG, Chao	20	17	3	0