AI科技論文研討(一)
Research Seminar on AI Technologies (I)
| 節 | 週二 |
|---|---|
5 13:20–14:10 | AI科技論文研討(一) M105（光復） 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
本課程將介紹近年AI科技相關的研究發展,尤其著重在商業數據分析和資料科學上的應用。本課程的主要目標為培養研究生進階的科學研究方法,進而能擁有AI領域論文寫作的能力。
管理資訊系統,人工智慧,商業智慧分析應用,機器學習商業應用,且修習過Python及統計相關課程。
無備註
助教
課堂參與30%,個人期末報告(口頭)10%,個人期末報告(書面)60%
資料科學
1. Application of AI, blockchain, cloud and data analytics 2. Predictive analytics 3.ML & NLP
- 講授：
- 24
商業智慧分析應用
1. Business value from big data analytics 2. Business Intelligence
- 講授：
- 24
| 週次 | 主題 |
|---|---|
| 第 1 週 | Abbasi, A., Sarker, S., & Chiang, R. H. (2016). Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17(2), 3. 9/16 |
| 第 2 週 | Grover, V., Chiang, R. H., Liang, T. P., & Zhang, D. (2018). Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems, 35(2), 388-423. 9/23 |
| 第 3 週 | Trieu, V. H. (2017). Getting value from Business Intelligence systems: A review and research agenda. Decision Support Systems, 93, 111-124. 9/30 |
| 第 4 週 | Lim, E. P., Chen, H., & Chen, G. (2013). Business intelligence and analytics: Research directions. ACM Transactions on Management Information Systems (TMIS), 3(4), 1-10. 10/7 |
| 第 5 週 | Mikalef, P., Pappas, I. O., Krogstie, J., & Giannakos, M. (2018). Big data analytics capabilities: a systematic literature review and research agenda. Information Systems and e-Business Management, 16(3), 547-578. 10/14 |
| 第 6 週 | Côrte-Real, N., Oliveira, T., & Ruivo, P. (2017). Assessing business value of Big Data Analytics in European firms. Journal of Business Research, 70, 379-390. 10/21 |
| 第 7 週 | Storey, V. C., & Song, I. Y. (2017). Big data technologies and management: What conceptual modeling can do. Data & Knowledge Engineering, 108, 50-67. 10/28 |
| 第 8 週 | Akter, S., Michael, K., Uddin, M. R., McCarthy, G., & Rahman, M. (2020). Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics. Annals of Operations Research, 1-33. 11/4 |
| 第 9 週 | Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77-84. 11/11 |
| 第 10 週 | Mikalef, P., Pappas, I. O., Krogstie, J., & Pavlou, P. A. (2020). Big data and business analytics: A research agenda for realizing business value. Information & Management, 57(1), 103237. 11/18 |
| 第 11 週 | Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment?. International Journal of Production Economics, 182, 113-131. 11/25 |
| 第 12 週 | Fan, S., Lau, R. Y., & Zhao, J. L. (2015). Demystifying big data analytics for business intelligence through the lens of marketing mix. Big Data Research, 2(1), 28-32. 12/2 |
| 第 13 週 | Saggi, M. K., & Jain, S. (2018). A survey towards an integration of big data analytics to big insights for value-creation. Information Processing & Management, 54(5), 758-790. 12/9 |
| 第 14 週 | Müller, O., Fay, M., & Vom Brocke, J. (2018). The effect of big data and analytics on firm performance: An econometric analysis considering industry characteristics. Journal of Management Information Systems, 35(2), 488-509. 12/16 |
| 第 15 週 | 期末口頭報告與討論 12/23 |
| 第 16 週 | 期末口頭報告與討論 12/30 |
| 第 17 週 | 期末口頭報告與討論 1/6 |
| 第 18 週 | 期末口頭報告與討論 1/13 |
每週指定閱讀文獻
- 地點
- 上課教室
- 時間
- 週四 5 – 6 pm
- 聯絡方式
- By E3 or email