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

111-2 317130 人工智慧、企業與社會 1 3.0 3 ★ 張瑋倫經管所
管理外國學生專班
國際金融科技專班
管理博所 51 1 經管所、管理博和IMBA&IMFI合開

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
111-2	317130	人工智慧、企業與社會	1	3.0	3	★	張瑋倫	經管所管理外國學生專班國際金融科技專班管理博所	51	1	經管所、管理博和IMBA&IMFI合開

教學大綱與進度：

教師姓名張瑋倫　教師諮商時間(Office Hours)

Email wlchang@ntut.edu.tw

最後更新時間 2022-12-19 19:12:48

課程大綱 This course provides an overview of AI and its role in business transformation. The purpose is to improve understanding of AI and being used in the industries. The brief technical overview of AI will be covered such as big data, data mining, machine learning, etc. The objectives are to learn how digital technologies will be applied to various business settings and how to adapt business strategy and operation in the era of digital transformation. Finally, learning how to utilize AI as the source of competitive advantage.

課程進度 W1: Orientation W2: AI for Business Course Intro (Is AI a General Purpose Technology?) W3: Intro to Big Data and AI W4: Understanding the use of AI in business (chap 2&3 of T2) W5: AI (Machine Learning) (chap 4&5 of T1) W6: Business Applications of Machine Learning (chap 3 of T1) W7: OFF W8: Psychology of algorithm (chap 6&7 of T1) W9: AI-driven strategy (chap 4 of T2) W10: Midterm week W11: Building and Investing in AI-Based Businesses (R4) W12: Introduction to Business Analytics (R5, R6, R7) W13: AI tasks, organizational structures, and business processes (chap 5 of T2) W14: Jobs and skills in a world of smart machines (chap 6 of T2) W15: Risks with AI (chap 10 of T1) W16: Organizational, social, and ethical implications (chap 8 of T2) W17: Final Presentation

評量方式與標準 Final project presentation: 60% Attendance: 10% Assignments: 30%

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
Textbook: T1. A Human’s Guide to Machine Intelligence by Kartik Hosanagar T2: The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge) Other supplements: R1.Brynjolfsson E, McAfee A. 2017. The Business of Artificial Intelligence. Harvard Business Review. Available at: https://hbr.org/cover-story/2017/07/the-business-of-artificialintelligence. R2.Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-Powered Organization. Harvard Business Review, 97(August), 1–13. • Hagiu, A., & R3.Wright, J. (2020). When Data Creates Competitive Advantage. Harvard Business Review, 98(January–February), 94–102. R4.Venkat Srinivasan, “Context, Language, and Reasoning in AI: Three Key Challenges,” MIT Technology Review, October 4, 2016 (https://www.technologyreview.com/2016/10/14/156968/context-language-and-reasoning-in-ai-three-key-challenges/) R5.Davenport article - “Competing on Analytics” (Harvard Business Review) R6.LaValle et al. article - “Analytics: The New Path to Value” (MIT Sloan Management Review) R7.Davenport and Harris article - “The Dark Side of Customer Analytics” (Harvard Business Review) R8. Loveman article – “Diamonds in the Data Mine” (Harvard Business Review)

課程諮詢管道 Please contact via email: wlchang@ntut.edu.tw

備註
Google Meet + Google Classroom

教師姓名	張瑋倫　教師諮商時間(Office Hours)
Email	wlchang@ntut.edu.tw
最後更新時間	2022-12-19 19:12:48
課程大綱	This course provides an overview of AI and its role in business transformation. The purpose is to improve understanding of AI and being used in the industries. The brief technical overview of AI will be covered such as big data, data mining, machine learning, etc. The objectives are to learn how digital technologies will be applied to various business settings and how to adapt business strategy and operation in the era of digital transformation. Finally, learning how to utilize AI as the source of competitive advantage.
課程進度	W1: Orientation W2: AI for Business Course Intro (Is AI a General Purpose Technology?) W3: Intro to Big Data and AI W4: Understanding the use of AI in business (chap 2&3 of T2) W5: AI (Machine Learning) (chap 4&5 of T1) W6: Business Applications of Machine Learning (chap 3 of T1) W7: OFF W8: Psychology of algorithm (chap 6&7 of T1) W9: AI-driven strategy (chap 4 of T2) W10: Midterm week W11: Building and Investing in AI-Based Businesses (R4) W12: Introduction to Business Analytics (R5, R6, R7) W13: AI tasks, organizational structures, and business processes (chap 5 of T2) W14: Jobs and skills in a world of smart machines (chap 6 of T2) W15: Risks with AI (chap 10 of T1) W16: Organizational, social, and ethical implications (chap 8 of T2) W17: Final Presentation
評量方式與標準	Final project presentation: 60% Attendance: 10% Assignments: 30%
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 Textbook: T1. A Human’s Guide to Machine Intelligence by Kartik Hosanagar T2: The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge) Other supplements: R1.Brynjolfsson E, McAfee A. 2017. The Business of Artificial Intelligence. Harvard Business Review. Available at: https://hbr.org/cover-story/2017/07/the-business-of-artificialintelligence. R2.Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-Powered Organization. Harvard Business Review, 97(August), 1–13. • Hagiu, A., & R3.Wright, J. (2020). When Data Creates Competitive Advantage. Harvard Business Review, 98(January–February), 94–102. R4.Venkat Srinivasan, “Context, Language, and Reasoning in AI: Three Key Challenges,” MIT Technology Review, October 4, 2016 (https://www.technologyreview.com/2016/10/14/156968/context-language-and-reasoning-in-ai-three-key-challenges/) R5.Davenport article - “Competing on Analytics” (Harvard Business Review) R6.LaValle et al. article - “Analytics: The New Path to Value” (MIT Sloan Management Review) R7.Davenport and Harris article - “The Dark Side of Customer Analytics” (Harvard Business Review) R8. Loveman article – “Diamonds in the Data Mine” (Harvard Business Review)
課程諮詢管道	Please contact via email: wlchang@ntut.edu.tw
備註	Google Meet + Google Classroom