Course Syllabus

Course Information：

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

Spring Semester
Year 2026 356233 Intelligent Production Technology 1 3.0 3 ★ LI, CHIH-HUNG GME
GMT
IMMA
半導體學位學程
DME
機電外國學生專班 76 0 乙◎機電.製科.半導體碩班.機械自動化.機電博含外生班

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2026	356233	Intelligent Production Technology	1	3.0	3	★	LI, CHIH-HUNG	GME GMT IMMA 半導體學位學程 DME 機電外國學生專班	76	0	乙◎機電.製科.半導體碩班.機械自動化.機電博含外生班

Course Plan：

Instructor LI, CHIH-HUNG

Email cl4e@mail.ntut.edu.tw

Last Updated 2026-03-06 17:59:38

Course Objective This course covers a wide range of fundamental technologies pertinent to Industry 4.0-Intelligent production, including a brief history of the industrial revolution, artificial intelligence algorithms, technologies and application examples of the Internet of Things, cloud service systems and information security technologies, big data management, analysis, and application examples, intelligent enterprise and factory management systems and applications, automation and robotics technology and applications, etc.

Course Schedule Week 1 Introduction to Intelligent Production Week 2 The Past and Present of Artificial Intelligence Week 3 Principles of Contemporary Artificial Intelligence Week 4 Intelligent enterprise and factory management system and application Week 5 IoT basic technology and application Week 6 Cloud Service System and Information Security Technology Week 7 Mass data management, analysis, and application Week 8 Value creation system Week 9 Mid-term examination Week 10 Special topic: Prognostic Maintenance Week 11 Special topic: IoT in Industry 4.0 Week 12 Special topic: Industrial IoT Week 13 Special topic: Cloud Manufacturing Week 14 Special topic: Digital Twin in Manufacturing Week 15 Special topic: Machine Learning and Data Mining in Manufacturing Week 16 Special topic: Defect Detection Week 17 Special topic: Cyber-Physical Systems Week 18 Final exam

Evaluation and grading policy Report grade: 60% Mid-term exam: 20% Final exam: 20%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Industry 4.0 - Intelligent Production Technology and Practice, Chih-Hung Li (Teacher's notes) Machine Learning/Tom M. Mitchell/McGraw-Hill Deep Learning/Ian Goodfellow, Yoshua Bengio, Aaron Courville/MIT Press (http://www.deeplearningbook.org)

The access to curricular consultation Place: Room 714-2, Integrated Technology Complex
Time: Fri:8:00-12:00

Expanding teaching and resources ● 參與式創新教學 (Participatory & Innovative Teaching)
強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。
Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification.
● 數位科技融入 (Digital Technology Integration)
運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。
Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.

The course corresponds to the SDGs SDG7：可負擔的潔淨能源（Affordable and Clean Energy）
SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth）
SDG12：負責任的消費與生產（Responsible Consumption and Production）

Does the course incorporate AI ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）
● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）

Note
7.可負擔能源Affordable and Clean Energy
8.就業與經濟成長Decent Work and Economic Growth
12.責任消費與生產Responsible Consumption and Production

Instructor	LI, CHIH-HUNG
Email	cl4e@mail.ntut.edu.tw
Last Updated	2026-03-06 17:59:38
Course Objective	This course covers a wide range of fundamental technologies pertinent to Industry 4.0-Intelligent production, including a brief history of the industrial revolution, artificial intelligence algorithms, technologies and application examples of the Internet of Things, cloud service systems and information security technologies, big data management, analysis, and application examples, intelligent enterprise and factory management systems and applications, automation and robotics technology and applications, etc.
Course Schedule	Week 1 Introduction to Intelligent Production Week 2 The Past and Present of Artificial Intelligence Week 3 Principles of Contemporary Artificial Intelligence Week 4 Intelligent enterprise and factory management system and application Week 5 IoT basic technology and application Week 6 Cloud Service System and Information Security Technology Week 7 Mass data management, analysis, and application Week 8 Value creation system Week 9 Mid-term examination Week 10 Special topic: Prognostic Maintenance Week 11 Special topic: IoT in Industry 4.0 Week 12 Special topic: Industrial IoT Week 13 Special topic: Cloud Manufacturing Week 14 Special topic: Digital Twin in Manufacturing Week 15 Special topic: Machine Learning and Data Mining in Manufacturing Week 16 Special topic: Defect Detection Week 17 Special topic: Cyber-Physical Systems Week 18 Final exam
Evaluation and grading policy	Report grade: 60% Mid-term exam: 20% Final exam: 20%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Industry 4.0 - Intelligent Production Technology and Practice, Chih-Hung Li (Teacher's notes) Machine Learning/Tom M. Mitchell/McGraw-Hill Deep Learning/Ian Goodfellow, Yoshua Bengio, Aaron Courville/MIT Press (http://www.deeplearningbook.org)
The access to curricular consultation	Place: Room 714-2, Integrated Technology Complex Time: Fri:8:00-12:00
Expanding teaching and resources	● 參與式創新教學 (Participatory & Innovative Teaching) 強調學生參與與產出，導入翻轉、PBL/專題、設計思考或遊戲化等策略。 Emphasizes student engagement and outcomes by adopting strategies such as Flipped Classroom, PBL (Problem/Project- Based Learning), Design Thinking, or Gamification. ● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
The course corresponds to the SDGs	SDG7：可負擔的潔淨能源（Affordable and Clean Energy） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG12：負責任的消費與生產（Responsible Consumption and Production）
Does the course incorporate AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI） ● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）
Note	7.可負擔能源Affordable and Clean Energy 8.就業與經濟成長Decent Work and Economic Growth 12.責任消費與生產Responsible Consumption and Production