Course Syllabus

Course Information：

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

Spring Semester
Year 2024 332345 Machine Learning -assisted Computer Auditing 1 3.0 3 ★ TSUI PENG GIFM
MPIS
MSIS
CMGT 20 1 資財四甲乙、資財所、創新資安、電資資安和管理博合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2024	332345	Machine Learning -assisted Computer Auditing	1	3.0	3	★	TSUI PENG	GIFM MPIS MSIS CMGT	20	1	資財四甲乙、資財所、創新資安、電資資安和管理博合開

Course Plan：

Instructor TSUI PENG　Office Hours

Email johnpeng@mail.ntut.edu.tw

Last Updated 2023-12-18 15:45:45

Course Objective 電腦稽核已廣泛的應用在金融交易，企業財務與進銷存流程與資訊系統的各項領域來協助找出瑕疵，降低與防範風險，並能做趨勢預測。本課程的目的將機器學習與人工智慧的技術應用在電腦稽核領域，主題包含: 電腦稽核的流程，大量資料的整理與萃取，監督式與非監督式學習在稽核的應用，資料視覺化技術等。 Computer auditing has been widely used in financial transactions, enterprise business processes, and information systems, which is to help find flaws and reduce risks, and be able to predict trends. The purpose of this course is to apply machine learning technology in the field of computer auditing. Topics include Computer auditing related processes, the extraction and manipulation of large-scaled data, supervised and unsupervised learning in auditing applications, data visualization technology.

Course Schedule week 1: Introduction, an overview of why, what, and how week 2-3 Workflow of computer auditing: various cases studies week 4-6 Data fetch and manipulation technologies: hands-on with google tools and low-code RPA tools week 7-8 Machine learning tools on dataset training and detection week 9 Mid-term report week 10-11 Unsupervised learning tools for auditing week 12-15 Data visualization week 16-18 Group project presentation

Evaluation and grading policy • Homework, class participation: 30% • Midterm report & presentation: 30% • Final project: 40%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:No
Low-code and no-code ML tools, such as https://blog.tensorflow.org/2022/12/introducing-simple-ml-for-sheets.html

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

The course website will be listed on
https://tipeng.wixsite.com/school/

The course corresponds to the SDGs

Does the course incorporate AI

Note
SDG8.9

Instructor	TSUI PENG　Office Hours
Email	johnpeng@mail.ntut.edu.tw
Last Updated	2023-12-18 15:45:45
Course Objective	電腦稽核已廣泛的應用在金融交易，企業財務與進銷存流程與資訊系統的各項領域來協助找出瑕疵，降低與防範風險，並能做趨勢預測。本課程的目的將機器學習與人工智慧的技術應用在電腦稽核領域，主題包含: 電腦稽核的流程，大量資料的整理與萃取，監督式與非監督式學習在稽核的應用，資料視覺化技術等。 Computer auditing has been widely used in financial transactions, enterprise business processes, and information systems, which is to help find flaws and reduce risks, and be able to predict trends. The purpose of this course is to apply machine learning technology in the field of computer auditing. Topics include Computer auditing related processes, the extraction and manipulation of large-scaled data, supervised and unsupervised learning in auditing applications, data visualization technology.
Course Schedule	week 1: Introduction, an overview of why, what, and how week 2-3 Workflow of computer auditing: various cases studies week 4-6 Data fetch and manipulation technologies: hands-on with google tools and low-code RPA tools week 7-8 Machine learning tools on dataset training and detection week 9 Mid-term report week 10-11 Unsupervised learning tools for auditing week 12-15 Data visualization week 16-18 Group project presentation
Evaluation and grading policy	• Homework, class participation: 30% • Midterm report & presentation: 30% • Final project: 40%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No Low-code and no-code ML tools, such as https://blog.tensorflow.org/2022/12/introducing-simple-ml-for-sheets.html
The access to curricular consultation	johnpeng@ntut.edu.tw The course website will be listed on https://tipeng.wixsite.com/school/
The course corresponds to the SDGs
Does the course incorporate AI
Note	SDG8.9