Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2025 344982 Financial Technology 1 3.0 3 ▲ Chen-Shu Wang
CHIEN-WEN WU
Sung-Shun Weng 雙聯EMBA 7 0 碩一必修王3/15-16、翁5/3-4、吳6/14-15

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2025	344982	Financial Technology	1	3.0	3	▲	Chen-Shu Wang CHIEN-WEN WU Sung-Shun Weng	雙聯EMBA	7	0	碩一必修王3/15-16、翁5/3-4、吳6/14-15

Course Plan：

Instructor Chen-Shu Wang　Office Hours

Email wangcs@ntut.edu.tw

Last Updated 2025-01-15 16:07:03

Course Objective 金融科技是近年來新興的產業趨勢，影響的層面非常廣泛，不只是金融方面，更牽涉到新興科技與物聯網。本課程將從不同的角度分析金融科技的技術內容、應用領域及商業模式，並藉由國內外重要金融科技公司發展的經驗做一介紹，希望達到了解並運用此新興科技的目的。本課程內容包括:金融科技概論、金融科技商業模式、金融大數據、P2P 借貸、虛擬貨幣、雲端服務、第三方支付、群眾募資、區塊鏈、跨境電商、程式交易、機器人理財等主題。 FinTech includes two words: Finance and Technology. It is a new trend of industrial field. It has influences on lots of technical fields, not only finance, but also emerging technologies and IoT. This course will analyze FinTech from different angles, such as technology contents, application fields and business models. It also will utilize experiences of leading companies with FinTech to obtain decent knowledge of this new field. The contents of this course include introduction to financial technology, business models of financial technology, finance big data, P2P lending, virtual money, cloud services, third-party payment, crowd funding, blockchain, cross-border e-commerce, program trading, and robotic financial advisory etc.

Course Schedule Topic: Topic 1: Data analytics of financial data - Introduction of financial Data analytics and Fintech - Data Analysis, KDD、SEMMA、CRISP-DM - 6 steps of Google data analytics - AI canvas Topic 2: Financial data analytics with open source - Weka Package (http://www.cs.waikato.ac.nz/ml/weka/) - Rapid Miner (https://rapidminer.com/products/studio/) Topic 3: Financial data analysis project - UCI Machine Learning Repository (https://archive.ics.uci.edu/ml/datasets.html) - Kaggle

Evaluation and grading policy Grade: - Assignment (Weka, Rapid Miner) 30% - Financial Data analytics Project 70%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:No
rapidminer

The access to curricular consultation wangcs@ntut.edu.tw

The course corresponds to the SDGs 無（None）

Does the course incorporate AI

Note
　

Instructor	Chen-Shu Wang　Office Hours
Email	wangcs@ntut.edu.tw
Last Updated	2025-01-15 16:07:03
Course Objective	金融科技是近年來新興的產業趨勢，影響的層面非常廣泛，不只是金融方面，更牽涉到新興科技與物聯網。本課程將從不同的角度分析金融科技的技術內容、應用領域及商業模式，並藉由國內外重要金融科技公司發展的經驗做一介紹，希望達到了解並運用此新興科技的目的。本課程內容包括:金融科技概論、金融科技商業模式、金融大數據、P2P 借貸、虛擬貨幣、雲端服務、第三方支付、群眾募資、區塊鏈、跨境電商、程式交易、機器人理財等主題。 FinTech includes two words: Finance and Technology. It is a new trend of industrial field. It has influences on lots of technical fields, not only finance, but also emerging technologies and IoT. This course will analyze FinTech from different angles, such as technology contents, application fields and business models. It also will utilize experiences of leading companies with FinTech to obtain decent knowledge of this new field. The contents of this course include introduction to financial technology, business models of financial technology, finance big data, P2P lending, virtual money, cloud services, third-party payment, crowd funding, blockchain, cross-border e-commerce, program trading, and robotic financial advisory etc.
Course Schedule	Topic: Topic 1: Data analytics of financial data - Introduction of financial Data analytics and Fintech - Data Analysis, KDD、SEMMA、CRISP-DM - 6 steps of Google data analytics - AI canvas Topic 2: Financial data analytics with open source - Weka Package (http://www.cs.waikato.ac.nz/ml/weka/) - Rapid Miner (https://rapidminer.com/products/studio/) Topic 3: Financial data analysis project - UCI Machine Learning Repository (https://archive.ics.uci.edu/ml/datasets.html) - Kaggle
Evaluation and grading policy	Grade: - Assignment (Weka, Rapid Miner) 30% - Financial Data analytics Project 70%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No rapidminer
The access to curricular consultation	wangcs@ntut.edu.tw
The course corresponds to the SDGs	無（None）
Does the course incorporate AI
Note