資料探勘與商業智慧
Data mining and Business Intelligence
| 節 | 週三 |
|---|---|
A 18:30–19:20 | 資料探勘與商業智慧 M101 3 節連堂 |
B 19:30–20:20 | |
C 20:30–21:20 |
* 根據陽明交大上課時間表所列
With the rapid development of artificial intelligence and big data analytics techniques, several innovative applications and novel business model are proposed to improve the daily operations of enterprises and business strategies. This course includes two major parts: (1) Data Mining: The courses in the first half semester introduces the theory and practices of data mining techniques. Data mining is an interdisciplinary research field which involves machine learning, statistics, and database management. It focuses on the pattern extraction and knowledge discovery from large data sets. (2) Business Intelligence: The remaining courses will let the students understand the emerging issues about business intelligence(BI). BI comprises the strategies and technologies used by enterprises for the data analysis of business information. Several important tools, including data visualization, report automation, data-driven decision making, will be discussed with the lectures, case study, and oral presentation.
Fundamental programming skills
Midterm exam 40% Class participation 10% Homeworks, group presentation and Final project 50%
- Business Intelligence
- Data mining
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course Introduction |
| 第 2 週 | Introduction to machine learning and data mining |
| 第 3 週 | Classification I |
| 第 4 週 | Classification II |
| 第 5 週 | KNN and Kmeans |
| 第 6 週 | Association Rules |
| 第 7 週 | Clustering |
| 第 8 週 | Anomaly Detection |
| 第 9 週 | Mid-term Exam |
| 第 10 週 | Service Design I |
| 第 11 週 | Service Design II |
| 第 12 週 | Business Plan Writing |
| 第 13 週 | Case Study I (Ubereats) |
| 第 14 週 | Case Study II (Tesla) |
| 第 15 週 | Case Study III (Post-covid-19 business intelligence) |
| 第 16 週 | Business Intelligence Final Report |
| 第 17 週 | On-line Seminar |
| 第 18 週 | On-line Seminar |
Han, J., Pei, J., & Tong, H. (2022). Data mining: concepts and techniques. 3/e, Morgan kaufmann.
- 地點
- Room 418, Management Building I
- 時間
- by appointment
- 聯絡方式
- szuhaohuang@nycu.edu.tw