查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

114-2 356233 智能化生產技術 1 3.0 3 ★ 李志鴻機電所
製科所
機械自動化外生專班
半導體學位學程
機電博所
機電外國學生專班 78 0 乙◎機電.製科.半導體碩班.機械自動化.機電博含外生班

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
114-2	356233	智能化生產技術	1	3.0	3	★	李志鴻	機電所製科所機械自動化外生專班半導體學位學程機電博所機電外國學生專班	78	0	乙◎機電.製科.半導體碩班.機械自動化.機電博含外生班

教學大綱與進度：

教師姓名李志鴻

Email cl4e@mail.ntut.edu.tw

最後更新時間 2026-03-06 17:59:38

課程大綱 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.

課程進度 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

評量方式與標準 Report grade: 60% Mid-term exam: 20% Final exam: 20%

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：是
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)

課程諮詢管道 Place: Room 714-2, Integrated Technology Complex
Time: Fri:8:00-12:00

延伸教學與資源 ● 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.

課程對應SDGs指標 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）

課程是否導入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）

備註
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

教師姓名	李志鴻
Email	cl4e@mail.ntut.edu.tw
最後更新時間	2026-03-06 17:59:38
課程大綱	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.
課程進度	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
評量方式與標準	Report grade: 60% Mid-term exam: 20% Final exam: 20%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：是 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)
課程諮詢管道	Place: Room 714-2, Integrated Technology Complex Time: Fri:8:00-12:00
延伸教學與資源	● 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.
課程對應SDGs指標	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）
課程是否導入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）
備註	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