本課程將介紹資料挖礦與大數據分析的理論方法與應用，並加入豐富的實務案例，具體說明如何應用資料挖礦與大數據分析技術以解決真實問題，深入淺出地剖析資料挖礦與大數據分析，內容涵蓋資料挖礦基本概念與資料準備、資料挖礦的方法與實證、資料挖礦與大數據分析的進階運用；此外，配合教材提供SAS與相關軟體與實作範例說明，使學生能實際應用 資料挖礦方法解決相關問題，進而提升大數據分析和數位決策能力。
This course will introduce the theoretical methods and applications of data mining and big data analysis, and add a wealth of practical cases to explain in detail how to apply data mining and big data analysis technology to solve real problems, and analyze data mining and big data in simple and easy-to-understand terms. Analysis, the content covers the basic concepts of data mining and data preparation, data mining methods and demonstrations, and advanced applications of data mining and big data analysis; in addition, SAS and related software and implementation examples are provided in conjunction with the textbook to enable students to can be applied practically Data mining methods solve related problems, thereby improving big data analysis and digital decision-making capabilities.
This course explores possibilities in using statistical data for creating models to assist managerial & health-care decisions-making. It will develop expertise in a standard set of statistical and graphical techniques, which will be useful in analyzing business and health-care related data.
This course explores possibilities in using statistical data for creating models to assist managerial & health-care decision-making. It will develop expertise in a standard set of statistical and graphical techniques, which will be useful in analyzing business and health-care related data.
沈葆聖(2002)，SAS統計軟體與資料分析(滄海書局)
Shen Baosheng (2002), SAS statistical software and data analysis (Canghai Bookstore)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 作業作業 Homework |
20 | |
| 課程參與課程參與 course participation |
10 | |
| 期中考期中考 midterm exam |
30 | |
| 期末報告期末報告 Final report |
40 |
