| 授業名 | Data Science & AI for Leaders |
|---|---|
| Course Title | Data Science & AI for Leaders |
| 担当教員 Instructor Name | Louie Wong |
| 授業形態 Class Type | 講義 Regular course |
| 授業形式 Class Format | On Campus |
| 単位 Credits | 2 |
| 言語 Language | EN |
| 学位 Degree | BBA |
| 開講情報 Terms / Location | 2026 UG Nisshin Term1 |
| コード Couse Code | NUC418_N26A |
授業の概要 Course Overview
Mission Statementとの関係性 / Connection to our Mission Statement
This course introduces students to how data science and artificial intelligence (AI) are used in real business and societal contexts. Using case-based discussions, students will learn how managers make decisions under uncertainty, how data and AI reshape organizational processes, and how ethical and governance issues arise when analytics and AI systems are deployed at scale.
授業の目的（意義） / Importance of this course
As organizations increasingly rely on data science and AI to support strategic and operational decisions, future business leaders need to understand, evaluate, and responsibly apply analytics and AI solutions. This course equips students with managerial insight into how data-driven technologies create value and risk across industries.
学修到達目標 / Achievement Goal
By the end of this course, students will be able to critically analyze data-driven business cases, evaluate AI-based strategies, and formulate managerial recommendations that consider organizational, ethical, and societal implications.
本授業の該当ラーニングゴール Learning Goals
*本学の教育ミッションを具現化する形で設定されています。
LG1 Critical Thinking
LG2 Diversity Awareness
LG3 Ethical Decision Making
LG4 Effective Communication
LG5 Business Perspectives (BSc)
LG6 Managerial Perspectives (BBA)
LG7 International Perspectives (BA)
LG2 Diversity Awareness
LG3 Ethical Decision Making
LG4 Effective Communication
LG5 Business Perspectives (BSc)
LG6 Managerial Perspectives (BBA)
LG7 International Perspectives (BA)
受講後得られる具体的スキルや知識 Learning Outcomes
Upon successful completion of this course, students will be able to:
- Explain core concepts of data science and AI in business contexts.
- Interpret data and AI-driven business decisions across multiple industries.
- Evaluate the organizational and strategic impact of data science and AI systems.
- Identify ethical, legal, and governance risks in data-driven initiatives.
- Communicate data-driven managerial recommendations effectively.
- Explain core concepts of data science and AI in business contexts.
- Interpret data and AI-driven business decisions across multiple industries.
- Evaluate the organizational and strategic impact of data science and AI systems.
- Identify ethical, legal, and governance risks in data-driven initiatives.
- Communicate data-driven managerial recommendations effectively.
SDGsとの関連性 Relevance to Sustainable Development Goals
Goal 4 質の高い教育をみんなに（Quality Education）
教育手法 Teaching Method
| 教育手法 Teaching Method | % of Course Time | |
|---|---|---|
| インプット型 Traditional | 20 % | |
| 参加者中心型 Participant-Centered Learning | ケースメソッド Case Method | 80 % |
| フィールドメソッド Field Method | 0 % | 合計 Total | 100 % |
事前学修と事後学修の内容、レポート、課題に対するフィードバック方法 Pre- and Post-Course Learning, Report, Feedback methods
授業スケジュール Course Schedule
第1日（Day1）
Designing Work with AI: Automation or Augmentation●使用するケース
Drishti Technologies Inc.: Managing Operations through Computer Vision, AI, and Video Analytics第2日（Day2）
Choosing Where AI Matters Most●使用するケース
Coursera’s Foray into GenAI第3日（Day3）
Democratizing AI Inside the Organization●使用するケース
Moderna: Democratizing Artificial Intelligence第4日（Day4）
Who Should Govern Digital Markets: People or Algorithms●使用するケース
Safeguarding Creativity in e-Commerce-Alibaba's Original Design Protection Program第5日（Day5）
AI for Public Safety and Legitimacy●使用するケース
ShotSpotter: AI and the Future of Law Enforcement Technology第6日（Day6）
Algorithms, Regulation, and Corporate Responsibility●使用するケース
Meta's Quagmire: AI Algorithms and Social Media's Legal-Ethical Maze第7日（Day7）
Global AI Competition and Strategy●使用するケース
DeepSeek: Can it Create and Capture a Blue Ocean in the AI Industry?成績評価方法 Evaluation Criteria
*成績は下記該当項目を基に決定されます。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
*クラス貢献度合計はコールドコールと授業内での挙手発言の合算値です。
| 講師用内規準拠 Method of Assessment | Weights |
|---|---|
| コールドコール Cold Call | 10 % |
| 授業内での挙手発言 Class Contribution | 60 % |
| クラス貢献度合計 Class Contribution Total | 70 % |
| 予習レポート Preparation Report | 10 % |
| 小テスト Quizzes / Tests | 0 % |
| シミュレーション成績 Simulation | 0 % |
| ケース試験 Case Exam | 0 % |
| 最終レポート Final Report | 20 % |
| 期末試験 Final Exam | 0 % |
| 参加者による相互評価 Peer Assessment | 0 % |
| 合計 Total | 100 % |
評価の留意事項 Notes on Evaluation Criteria
配布教材と教室における電子機器の利用マナーについて Guidelines for Classroom Technology and Proper Use of Course Materials
- ケースメソッド教育の中核は、積極的な参加と知識の共有です。この教育を支えるため参加者は授業中の電子機器（例：スマートフォン、ノートパソコン）の使用を制限するよう求められます。許可を得た場合でも、教室内では電子機器は、ケース討議に資する目的でのみ使用してください。授業中は、たとえケース討議に関連していても、検索エンジンや生成AIの使用は避けて下さい。
- 配布教材（ケースを含む）は指定された授業への参加以外の目的で利用しないで下さい。著者の権利、著作権、特定情報の機密性を保護するため、許可なく教材を個人や組織（生成AI を含む）に提供することはできません。このルールは、印刷物・電子教材のいずれにも適用されます。
- 詳細は「教室における電子機器の利用マナー・教材の適切な利用に関するガイドライン」を確認のうえ、教員の指示に従い、責任をもって遵守してください。
- Active participation and shared learning is at the core of the case method learning.Participants are asked to limit their use of electronic devices (e.g., laptops, smartphones) during classroom sessions in support of this model. Even with permission granted, devices should only be used in the classroom in service to the case discussion. Online searches and generative AI tools, even if related to the case discussion, are discouraged while class is in session.
- Students are prohibited from using the course materials (including cases) distributed by the university for any purpose other than participation in the designated class.Students must not input, process or test course materials with any artificial intelligence (AI) tools, bots, software, or platforms without the author’s permission. These actions violate the terms of use for the course materials and may also constitute copyright infringement.
- Please refer to the "Classroom Technology Guidelines / Guidelines for Properly Using Course Materials” for details, and follow the instructor’s directions. You are expected to comply with these guidelines responsibly.
教科書 Textbook
- 「 」 （-）
参考文献・資料 Additional Readings and Resource
An Introduction to Data Science/AI for the Nontechnical Person
https://hbsp.harvard.edu/product/BEP646-PDF-ENG
https://hbsp.harvard.edu/product/BEP646-PDF-ENG
授業調査に対するコメント Comment on Course Evaluation
担当教員のプロフィール About the Instructor
Louie Wong is a Professor and an Associate Dean at NUCB Business School, Nagoya University of Commerce and Business, Japan. He received his PhD in Information Systems from the City University of Hong Kong, where he currently serves as an Adjunct Professor. Louie’s research focus on the intersection of technology and human behaviour. His research interests include action research, AI in business, digital leadership, digital transformation, social media and supply chain management. His research has been published in Information & Management, Information Systems Journal, International Journal of Information Management, Journal of Information Technology among others. Louie is currently an associate editor at Information Systems Journal.
（実務経験 Work experience）
Besides, Louie is also a seasoned business executive with decades of industry experience in the Asia Pacific region. Prior to his academic career, Louie served in various senior management positions at leading multinational companies such as Digital Equipment Corporation (DEC), Compaq, Check Point Technologies, and Citrix. His last industry position was the Chief Marketing Officer of a listed company in the new media industry.
Refereed Articles
- (2026) The impact of enterprise and public social media use on guanxi formation and task performance. International Journal of Information Management 88 0268-4012 online:1873-4707
- (2026) A Study on the Collection and Utilization of Product and Service Development by SME. Development Engineering 45(1): 1343-7623
- (2025) The impact of social media on digital guanxi development in the Chinese workplace: A technology affordance perspective. International Journal of Information Management 84 0268-4012 online:1873-4707
- (2024) Combining Low-Code/No-Code with Noncompliant Workarounds to Overcome a Corporate System’s Limitations. MIS Quarterly Executive 23(3): 1540-1960
- (2023) Instant messaging, interruptions, stress and work performance. Information Technology & People 0959-3845
Refereed Proceedings
- (2025). Digital Leadership in Motion: Guanxi Practices in Chinese Digital Transformation. ICIS 2025 Proceedings .International Conference on Information Systems (ICIS). 1. 3. Nashville, US
- (2023). Spearheading Digital Transformation: The Role of the Chief Digital Officer. PACIS 2023 Proceedings .Pacific Asia Conference on Information Systems (PACIS) 2023. 1. 3. Nanchang, China
- (2023). Developing Guanxi Through Social Media: User Archetypes and Influencing Factors. ECIS 2023 Research-in-Progress Papers .The 31st European Conference on Information Systems (ECIS), Kristiansand, Norway. 1. 3. Kristiansand, Norway
- (2023). The Impact of Social Media on Digital Guanxi Development in the Chinese Workplace. Proceedings of the 56th Hawaii International Conference on System Sciences .The Impact of Social Media on Digital Guanxi Development in the Chinese Workplace. 1. 3. Maui, Hawaii, USA
- (2020). Beneficial Non-Compliance with Inadequate Information Systems. International Conference on Information Systems (ICIS) 2020 Proceedings .International Conference on Information Systems (ICIS) 2020. 1. 3. India