ZHAO, Mingxuan - 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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Notes & Links
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

PRE-REQUISITE	DSAA 2011
DESCRIPTION	Financial Data Analysis explores state-of-the-art approaches for extracting insights and building AI-driven intelligent systems using diverse financial data sources. Students will engage in hands-on projects that involve analyzing and modeling multimodal financial data, including time-series (e.g., stock prices), textual data (e.g., news and social media), graph data (e.g., supply chain), tabular data (e.g., company fundamentals), and alternative data (satellite images). Drawing on tools from artificial intelligence and statistical modeling, students will learn to design and evaluate data-driven solutions to real-world financial tasks such as market prediction, sentiment analysis, and risk estimation. Through guided projects and open-ended problem-solving, students will gain experience in end-to-end data workflows, from acquisition and preprocessing to modeling and evaluation. The course emphasizes implementation and experimentation, preparing students for future research and industry roles in FinTech.

PRE-REQUISITE

DSAA 2011

DESCRIPTION

Financial Data Analysis explores state-of-the-art approaches for extracting insights and building AI-driven intelligent systems using diverse financial data sources. Students will engage in hands-on projects that involve analyzing and modeling multimodal financial data, including time-series (e.g., stock prices), textual data (e.g., news and social media), graph data (e.g., supply chain), tabular data (e.g., company fundamentals), and alternative data (satellite images). Drawing on tools from artificial intelligence and statistical modeling, students will learn to design and evaluate data-driven solutions to real-world financial tasks such as market prediction, sentiment analysis, and risk estimation. Through guided projects and open-ended problem-solving, students will gain experience in end-to-end data workflows, from acquisition and preprocessing to modeling and evaluation. The course emphasizes implementation and experimentation, preparing students for future research and industry roles in FinTech.

FTEC 4320 - Financial Data Analysis (3 units)

Section	Date & Time	Room	Instructor	Quota	Enrol	Avail	Wait	Remarks
L01 (6406)	We 09:00AM - 11:50AM	Rm 223, W1	SUN, Shuo ZHAO, Mingxuan	30	18	12	0
T01 (6407)	Fr 06:00PM - 06:50PM	Rm 201, W2	SUN, Shuo ZHAO, Mingxuan	30	18	12	0