| Year | Semester | Required Elective | Course ID | Course Name | Credits | Hours | Level | Note |
|---|---|---|---|---|---|---|---|---|
| 1 | 1 | ▲ | 3705035 | Journal Study and Discussion | 1.0 | 2 | ||
| 1 | 1 | ▲ | 3707001 | Thesis | 3.0 | 3 | 1 / 2 | |
| 1 | 1 | ★ | 1400510 | Advanced Practical English | 0.0 | 2 | ||
| 1 | 1 | ★ | 3705033 | Graduate On-Site Research | 3.0 | 18 | ||
| 1 | 1 | ★ | 3705036 | Industrial Engineering and Management Workshop (I) | 1.0 | 2 | ||
| 1 | 1 | ★ | 3706025 | Experimental Designs | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3706029 | Research Methodology | 3.0 | 3 | ■□ | |
| 1 | 1 | ★ | 3706040 | Industrial Robot | 3.0 | 3 | ◎ | |
| 1 | 1 | ★ | 3706078 | Scheduling Theory | 3.0 | 3 | ◎ | |
| 1 | 1 | ★ | 3706090 | Internet entrepreneurial management | 3.0 | 3 | □ | |
| 1 | 1 | ★ | 3714011 | Cognitive Human Factors | 3.0 | 3 | □ | |
| 1 | 1 | ★ | 3715003 | Taguchi Quality Engineering | 3.0 | 3 | ◎ | |
| 1 | 1 | ★ | 3715011 | OPERATIONS MANAGEMENT | 3.0 | 3 | ◎ | |
| 1 | 1 | ★ | 3725009 | Practices and applications of TRIZ innovative thinking | 3.0 | 3 | ◎ | |
| 1 | 1 | ★ | 3725012 | Introduction to IoT | 3.0 | 3 | □ | |
| 1 | 1 | ★ | 3725013 | VR/AR applications in workspace and its design | 3.0 | 3 | □ | |
| 1 | 1 | ★ | 3725014 | User Experience Data Collection and Analysis | 3.0 | 3 | □ | |
| 1 | 1 | ★ | 3725015 | E-commerce management | 3.0 | 3 | □ | |
| 1 | 1 | ★ | 3735002 | Supply Chain Coordination Management | 3.0 | 3 | ◎□ | |
| 1 | 1 | ★ | 3735005 | Scientific learning and Applications | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3735006 | Advanced Statistics with Applications | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3735007 | Advanced Engineering Economics | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3735008 | Advanced Statistics | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3735009 | Data Pattern Recognition and Classification | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3736001 | Industry Analysis | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3736017 | E-Business Management | 3.0 | 3 | □ | |
| 1 | 1 | ★ | 3736029 | Project Investment Analysis | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3736034 | Numerical Methods | 3.0 | 3 | ■□ | |
| 1 | 1 | ★ | 3736035 | Applications of Artificial Neural Networks | 3.0 | 3 | ■ | |
| 1 | 1 | ★ | 3737002 | Advanced Operations Research | 3.0 | 3 | ■ | |
| 1 | 2 | ▲ | 3705034 | Business Ethics | 1.0 | 2 | ||
| 1 | 2 | ▲ | 3707001 | Thesis | 3.0 | 3 | 2 / 2 | |
| 1 | 2 | ★ | 3705009 | Machine Learning | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3705014 | Human-Computer Interaction | 3.0 | 3 | □ | |
| 1 | 2 | ★ | 3705037 | Industrial Engineering and Management Workshop (Ⅱ) | 1.0 | 2 | ||
| 1 | 2 | ★ | 3706024 | Artificial Intelligence | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3706034 | Logistics Management | 3.0 | 3 | ◎ | |
| 1 | 2 | ★ | 3706041 | The Principles and Applications of Machine Vision | 3.0 | 3 | □◎ | |
| 1 | 2 | ★ | 3706082 | E-Business | 3.0 | 3 | □ | |
| 1 | 2 | ★ | 3706084 | Inventory Theory | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3706085 | Robotic Integrated Manufacturing | 3.0 | 3 | ◎ | |
| 1 | 2 | ★ | 3706087 | Supply Chain and Logistic Management | 3.0 | 3 | ◎□ | |
| 1 | 2 | ★ | 3706098 | Advanced Applied English | 0.0 | 2 | ||
| 1 | 2 | ★ | 3707009 | Optimization Methodology | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3715002 | Innovative Product R&D Management | 3.0 | 3 | ◎ | |
| 1 | 2 | ★ | 3715007 | The applications of TRIZ creative method | 3.0 | 3 | ◎ | |
| 1 | 2 | ★ | 3715008 | Fab Operation Management and Advanced Manufacturing Technology | 3.0 | 3 | ◎ | |
| 1 | 2 | ★ | 3715009 | Reliability Engineering | 3.0 | 3 | ◎ | |
| 1 | 2 | ★ | 3715012 | AR/VR Practice of Manufacturing and Workspace Design | 3.0 | 3 | ◎ | |
| 1 | 2 | ★ | 3723065 | Industry 4.0 Information System | 3.0 | 3 | □ | |
| 1 | 2 | ★ | 3725001 | automated inspection system | 3.0 | 3 | □ | |
| 1 | 2 | ★ | 3725004 | Internet Marketing | 3.0 | 3 | □◎ | |
| 1 | 2 | ★ | 3725010 | Psychophysics and Signal Detection Theory | 3.0 | 3 | □ | |
| 1 | 2 | ★ | 3725016 | Electronic Commerce；EC | 3.0 | 3 | □ | |
| 1 | 2 | ★ | 3725017 | Practice of Intelligent Manufacturing Execution System | 3.0 | 3 | □ | |
| 1 | 2 | ★ | 3735003 | Multi Objectives Decision Making | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3735004 | Artificial Intelligence and Machine Learning with Applications | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3736018 | Project Management | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3736036 | Seminar on Learning productivity | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3736038 | Network Models and Integer Programming | 3.0 | 3 | ■ | |
| 1 | 2 | ★ | 3737003 | Quality Management | 3.0 | 3 | ■ |
|
1. Minimum number of credits for the master degree: 35 credits 2. Required courses: 8 credits, including 6 credits from Master Thesis and 2 credits from Journal Study and Discussion; elective courses: 27 credits. 3. The master students can take at most 12 credits in other departments and institutes in National Taipei University of Technology or other universities. 4. The master students who did not obtain the bachelor degree from Industrial Engineering or related programs must take two of five courses: Production Planning and Control, Quality Management, Operations Research, Work Study, and Human Factors. The final scores of the two selected courses must exceed 70. 5. The courses are divided into three professional categories: Production Management and Manufacturing Services, E-Industry and the Application of Information, and Management Science and Decisions. The master students must take at least 4 courses from one of the three categories. Graduate On-Site Research belongs to all of the three categories. 6. The master students who enrolled in and after the academic year of 2009 must satisfy the degree requirement in English capability. The detailed information of the requirement can be found on the website of the department. 7. Each graduate student shall pass the minimum English proficiency requirement(s) for graduation, and shall all meet the criteria of the English proficiency tests set by the department (if any). Students may refer to the department websites for their English proficiency criteria set by each department. 8.The above table of courses is applied to the master students enrolled in the academic year of 2019. |