NTNU NTNU College of Management

Business Data Analysis (CMI)
Inter-Disciplinary Program

Business Analytics

Business Analysis

Strengthening Data Application Practices

01.Program Features

This program focuses on data analysis and application within the business sector. Beyond theoretical models and computational instruction, it emphasizes the management implications and practical applications of business data analysis, aiming to cultivate industry-ready data analysis talent. By completing this program, students will be able to study the impact of business data analysis on corporate strategy from various perspectives, such as fintech risk assessment and consumer behavior (online and offline), thereby enhancing their understanding and practical application across different business domains. The program also includes a capstone course, "Data Science and Management Decision-Making," in which students are required to complete a data-driven project using Markdown to create a reproducible document, covering the entire process from data collection to decision deployment. [Post-certification system applied]

02.Program Requirements

National Taiwan Normal University (hereinafter referred to as the University) has established the "Business Analytics Credit Program" (hereinafter referred to as the Program) in accordance with the University’s Credit Program Guidelines, aiming to cultivate business data analysis and application talent. The curriculum is jointly planned by the College of Management, Graduate Institute of Management, Graduate Institute of Global Business and Strategy, and the Department of Business Administration, with the College of Management as the primary organizer.
The program requires a minimum of 12 credits, consisting of 3 compulsory credits and 9 elective credits. Detailed course information can be found in the "Business Analytics Credit Program Curriculum."
Courses previously completed and passed that are identical or similar to the program courses may be credited after review by the organizing unit. However, the maximum number of credits that can be recognized is 6.
The University’s credit program follows a certification system. Eligible students may register for the program through the academic system during the designated registration period in the second semester of each academic year. Registered students will have priority in course selection during the initial selection period. Upon completing the program’s required courses and credits, students should submit an application form and academic transcripts to the organizing unit for review. After approval, the Office of Academic Affairs will issue a certificate of completion.
For students who have registered for the program but have not yet completed the required courses and credits, or those who have not registered but have completed at least one-third of the program credits, they may apply for an extension of their study period. Otherwise, they will be considered as having forfeited the right to complete the program. However, those who have been admitted to master’s or doctoral programs in the Taiwan University System may apply to continue the program after enrollment.
Any matters not covered in these guidelines shall be handled in accordance with the University’s relevant regulations.
These guidelines shall be implemented after approval by the Academic Affairs Meeting and shall be subject to the same approval process for amendments.

Qualifications

Undergraduate, Master’s, and Doctoral students from all departments within the three-campus system, excluding graduating students.
Application

During the application period (when the system is open), please select up to 5 programs online to complete the registration process.
- NTNU Students: Log in to the Academic Administration Portal → Academic Affairs → Day Division Academic Information System (Student) → Credit Programs → Application
- NTU and NTUST Students: Log in to the Taiwan University System Student Academic System → Credit Program Online Application
Admission

In June each year, check the system for distribution and admission results. Once admitted, the qualification to enroll in courses is automatically granted; no separate registration is required.
- NTNU Students: Log in to the Day Division Academic Information System (Student) → Credit Programs → Qualification Inquiry
- NTU and NTUST Students: Log in to the Taiwan University System Student Academic System → Credit Program Online Application → Application Inquiry
Application Period

Every April, according to the announcement from the Office of Academic Affairs regarding Credit Program Applications.
NTNU Office of Academic Affairs
Organizer
College of Management Campus Map
Contact Information

Graduate Institute of Management - Secretary Xu
- Phone: 02-77493296
- Email: yenchi@ntnu.edu.tw
- Address: 1st Floor, Administrative Office, College of Management, No. 31, Shida Rd., Da’an Dist., Taipei City

1. Compulsory Courses: 3 Credits

Course Code	Course Title	Credits	Offering Department	Remarks
BAC9001	Data Science and Management Decision-Making	3	Department of Business Administration	Joint Undergraduate & Master

2. Elective Courses: At least 9 Credits

Field	Course Code	Course Title	Credits	Offering Department	Remarks
Fundamental Field	ITM0006	Advanced Statistics I	3	Department of Technology (Master’s)
	ISM0429	Database Management Research	3	Graduate Institute of Library and Information Science (Master’s)
	IAC9002	Data Mining	3	Global Business Program (Undergraduate)	Joint Undergraduate & Master
	IAC9001	Text Mining	3	Global Business Program (Undergraduate)	Joint Undergraduate & Master
	BAC9002	Business Analytics Programming	3	Department of Business Administration (Undergraduate)	Joint Undergraduate & Master
	O5C9010	Econometrics and Applications	3	College of Management	Joint Undergraduate & Master
Application Field	MBC9001	Database Marketing	3	Graduate Institute of Management (Undergraduate)	Joint Undergraduate & Master
	MBC9002	Web Traffic Analysis and Marketing Practices	3	Graduate Institute of Management (Undergraduate)	Joint Undergraduate & Master
	MBC9004	Fintech and Applications	3	Graduate Institute of Management (Undergraduate)
	MBC9003	Business Data Visualization Design and Practice	3	Graduate Institute of Management (Undergraduate)	Joint Undergraduate & Master

1. Compulsory Courses: 3 Credits

Course Code	Course Title	Instructor	Time/Location	Remarks
BAC9001	Data Science and Management Decision-Making	Chen Meng-Ting	113-1 Thu 6-8 / Zheng 102	Joint Undergraduate & Master

2. Elective Courses: At least 9 Credits

Field	Course Code	Course Title	Instructor	Time/Location	Remarks
Fundamental Field	ITM0006	Advanced Statistics I	Chen Yi-Jing	113-2 Fri 2-4 / Dept. of Technology TB211
	ISM0429	Database Management Research	Hsieh Jian-Cheng	113-2 Mon 2-4 / LIS Seminar A
	IAC9002	Data Mining	Ho Zong-Wu	113-2 Thu 6-8 / Yun 608	Joint Undergraduate & Master
	IAC9001	Text Mining	Ho Zong-Wu	113-1 Fri 6-8 / Yun 508	Joint Undergraduate & Master
	BAC9002	Business Analytics Programming	Huang Hao-Ting	113-1 Thu 7-9 / Zhong 508	Joint Undergraduate & Master
	O5C9010	Econometrics and Applications	Xu Mei		Joint Undergraduate & Master
Application Field	MBC9001	Database Marketing	Zhou Shiyu		Joint Undergraduate & Master
	MBC9002	Web Traffic Analysis and Marketing Practices	Zhang Jia-Rong	113-1 Mon 6-8 / Zhong 509	Joint Undergraduate & Master
	MBC9004	Fintech and Applications	Gao Zhi-Yan		Joint Undergraduate & Master
	MBC9003	Business Data Visualization Design and Practice	Huang Hao-Ting	113-1 Fri 6-8 / Zheng 403	Joint Undergraduate & Master

	NTNU Graduate Students Demonstrate Strong Research Capabilities in Language Analysis and AI Applications Graduate students from the College of Management and the Department of Business Administration at NTNU anonymously submitted papers to the 2025 "@AI: Disrupt or Strengthen Communication Research" conference. The topics covered sustainable development, film text analysis, digital marketing, and sociolinguistic issues, showcasing innovative thinking through interdisciplinary integration. Professor Ho Tsung-Wu, Deputy Director of the Graduate Institute of Global Business and Strategy and session chair, noted that NTNU students demonstrated exceptional strength in language text applications and research! (Read More)	NTNU Graduate Students Demonstrate Strong Research Capabilities in Language Analysis and AI Applications NTNU graduate students and business administration students anonymously submitted papers to the 2025 "@AI: Disrupt or Strengthen Communication Research" conference, covering topics on sustainable development, film text analysis, digital marketing, and sociolinguistics. These themes exemplify innovative thinking through interdisciplinary integration. Professor Ho Tsung-Wu, Deputy Director of the Graduate Institute of Global Business and Strategy and session chair, emphasized that NTNU students displayed robust research capabilities in language text applications! In the session "AI-Driven Language Analysis and Social Insights," four students presented papers that covered topics including sustainable development, film text analysis, digital marketing, and sociolinguistics, demonstrating innovative interdisciplinary integration: ● Lu Xun-Xuan, a master's student from the Graduate Institute of Management, presented "Applying Text Mining Techniques to Thematic Analysis of Sustainability Reports," utilizing the LDA topic model to analyze sustainable development trends in the semiconductor and financial sectors. ● Chiu Yun-Chen, a master's student from the Graduate Institute of Global Business and Strategy, presented "Emotional and Thematic Analysis of Series Films: A Case Study of Jumanji," analyzing viewer comments to assess the potential for a second sequel. ● Chen Li-Han, a master's student from the Graduate Institute of Global Business and Strategy, presented "YouTube Influencer Trend Model: Focusing on Text Mining Analysis Using the E-Sports Industry as a Case Study," extracting comment threads against the number of likes to build a predictive text model. ● Yang Jia-Xiang, an undergraduate student from the Department of Business Administration, presented "Decoding Social Issues: Text Mining Analysis of Constitutional Court Debates on Capital Punishment," extracting key phrases from debate videos and using LDA topic modeling to showcase the narrative connections between key figures on both sides of the capital punishment debate. More details: https://pr.ntnu.edu.tw/ntnunews/index.php?mode=data&id=23332
	Data Analytics Leads the Future: NTNU College of Management’s “Business Analytics Credit Program” Achieves Outstanding Results With the rise of data science, business analytics has become a key competitive advantage for modern enterprises. Last year, the College of Management at National Taiwan Normal University launched the “Business Analytics Credit Program,” dedicated to cultivating professionals with data analysis and practical application capabilities. This program equips students with the analytical skills needed in today’s business environment and enables them to leverage data-driven insights to support corporate decision-making in dynamic market conditions. Owing to the program's success, Professor Ho Tsung-Wu was invited to the Taiwan Economic Association Annual Lecture at the end of last year to provide an in-depth explanation of text mining applications in economics. Four students who enrolled in this program were further invited to share their research findings at the “2025 @AI: Disrupt or Strengthen Communication Research” seminar held at Shih Hsin University. (Read More)	Data Analytics Leads the Future: NTNU College of Management’s “Business Analytics Credit Program” Achieves Outstanding Results With the rise of data science, business analytics has become a key competitive advantage for modern enterprises. Last year, the College of Management at NTNU introduced the “Business Analytics Credit Program,” which is committed to training professionals with data analytics and practical application abilities, helping students master the analytic techniques required by the current business world and apply data insights to drive enterprise decision-making in a volatile market environment. Thanks to the success of this program, Professor Ho Tsung-Wu was invited to deliver an in-depth lecture on text mining in economics at the Taiwan Economic Association's annual lecture at the end of last year. Moreover, four students who have taken this credit program were invited to present their research at the “2025 @AI: Disrupt or Strengthen Communication Research” seminar at Shih Hsin University. In his lecture, Professor Ho provided a detailed analysis of the applications of text mining in economics. He explained how to select appropriate textual data sources to enhance the practical application value of text mining techniques in economic forecasting. He further noted that research on the application of text mining in economics is currently scarce, and he was delighted to see growing interest in this topic within Taiwan’s academic community, especially among economists. He hopes this sparks more research potential in Taiwan in the future. More details: https://pr.ntnu.edu.tw/ntnunews/index.php?mode=data&id=23293
	Experiences in Internet Traffic Analysis and Marketing Practice Course Presenter: Lin Meng-Zhen, Year 4, Department of Business Administration The Internet Traffic Analysis and Marketing Practice course focuses on in-depth analysis of online traffic and formulating corresponding strategies. By integrating internal and external data within the business ecosystem, students apply classroom learning to solve client problems. (Read More)	Experiences in Internet Traffic Analysis and Marketing Practice (MBC9002) Course Presenter: Lin Meng-Zhen, Year 4, Department of Business Administration In-depth internet traffic analysis and strategic recommendations The Internet Traffic Analysis and Marketing Practice course emphasizes how to perform comprehensive online traffic analysis and propose corresponding strategies. The curriculum covers principles, frameworks, case studies, and related applications. Through project execution, students gain the most efficient understanding and learning of internet traffic analysis. Integrating internal and external data within the business ecosystem In the first half of the course, the instructor uses presentations and past case studies as supplementary materials to teach internet traffic analysis concepts. The course is underpinned by two theoretical foundations: data integration and the business ecosystem. Interactive Q&A sessions help students internalize knowledge and resolve doubts. A unique aspect of this course is the opportunity to collaborate with businesses directly: students use classroom knowledge to solve real client challenges, and the outcomes are presented in midterm and final reports. The instructor evaluates performance based on the reports, making this a crucial component of the course. Applying classroom learning to solve client problems Throughout the semester, preparation for reports requires analyzing business issues faced by clients and providing relevant strategies, tactics, and techniques. Students often hold 5 to 6 group meetings or more outside class hours, sometimes visiting client sites to observe actual operations and deliver accurate, effective strategies. Consequently, the workload for this course is heavier compared to others. We recommend evaluating your total credit load before enrolling to avoid overcommitment or lack of time for group discussions, which could inconvenience teammates. Although the workload seems heavy, the sense of achievement and gains from completing this course are immense. Additionally, this course is not offered every year; if you have the opportunity, be sure to enroll!
	Text Mining Course Experience Presenter: Yang Jia-Xiang, Year 4, Department of Business Administration From tokenization to machine learning, this course lays a solid foundation in business analytics. Unlike courses that simply provide sample code and encourage you to click “Run, Run, Run…” without understanding results, this text mining course delves into the core of textual data processing, building a solid foundation from scratch. (Read More)	Text Mining (IAC9001) Course Experience Presenter: Yang Jia-Xiang, Year 4, Department of Business Administration From tokenization to machine learning: establishing a solid foundation in business analytics Unlike sessions that only provide example code and instruct constant clicking of “Run, Run, Run…,” often flashy but lacking clarity on outcomes, this text mining course guided me deep into the heart of textual data processing, establishing a rigorous foundation from the ground up. The course began with basic text preprocessing using the jieba tokenizer to analyze word structures and semantic meaning. Through TF-IDF keyword extraction, I quickly grasped core terms in texts and social media comments. The most intriguing was the LDA topic model, which demonstrated how algorithms can automatically decode article themes and reveal deeper insights. After laying a solid groundwork, supervised machine learning techniques were applied to quantify numeric and textual data, sparking creative possibilities in final projects that often surprised students. From sustainability reports to constitutional court debates: text mining everywhere Text surrounds us in countless forms—from corporate sustainability reports and social media comments to presidential speeches. Modern generative AI and large language models also build upon text mining fundamentals. Therefore, mastering text data processing skills is crucial for standing out in tomorrow’s workplace. In the final project, classmates’ works included analyses of sustainability reports, social media sentiment and viewership predictions, and film review box-office forecasts. My project focused on “Text Mining the Constitutional Court Debate on the Death Penalty,” and I conducted two primary analyses: 1. Extracted keywords from expert speeches on both sides to highlight the viewpoints and linguistic features associated with each stance, including a temporal analysis of argument usage. 2. Applied the LDA topic model to segment debate topics and measure each expert’s thematic relevance, revealing the aspects each expert prioritized. This course enriched my understanding of constitutional court debates and enabled me to complete a personal project, serving as the best testament to my business analytics capabilities.

Qualifications

Undergraduate, Master’s, and Doctoral students from all departments within the three-campus system, excluding graduating students.

Application

During the application period (when the system is open), please select up to 5 programs online to complete the registration process.

Admission

In June each year, check the system for distribution and admission results. Once admitted, the qualification to enroll in courses is automatically granted; no separate registration is required.

Application Period

Every April, according to the announcement from the Office of Academic Affairs regarding Credit Program Applications.

Organizer

Contact Information

Graduate Institute of Management - Secretary Xu