隨著網際網路以及資料庫技術的發達，人們搜尋資料變得愈來愈容易，透過網路我們可以輕易地獲取大量的資料，於是在資料充斥的情況之下，現代的資訊技術所要面臨的挑戰已經不是如何管理資料，而是如何從這些大量的資料當中，找出真正有用的資訊，而要滿足這個需求最主要的方法就是仰賴資料探勘的技術。資料探勘是一個利用各種分析工具在大量資料中發現模型和資料間關係的過程，使用這些模型和關係可以進行預測，它幫助決策者尋找資料間潛在的關聯，發現被忽略的因素，因而認為是解當今時代所面臨的資料爆炸而資訊貧乏問題的一種有效方法。
With the development of Internet and database technology, it is easier for people to search data. Through the Internet, we can easily obtain a large amount of data, so modern information technology is facing it under the influence of data. Challenges are no longer how to manage data, but how to find truly useful information from these large amounts of data, and the most important way to meet this requirement is to rely on the technology of data exploration. Data exploration is a process that uses various analytical tools to discover models and data relationships in a large amount of data. Using these models and relationships can be predicted. It helps decision makers find potential relationships between data and find ignored factors, so they are considered to be. An effective way to solve the data explosion faced by this era and lack of information problems.
讓學生知悉資料探勘如何運作，原理為何
Let students know how data exploration works and what principles
1.資料探勘 (旗標)
2.資料探勘原理與技術 (五南)
3.資料探勘─人工智慧與機器學習發展-以 SPSS Modeler為範例 (博碩文化)
4.資料探勘 (滄海)
5.資料探勘 (PEARSON, 歐亞書局代理)
1. Data Exploration (Flag)
2. Principles and Technology of Data Exploration (Wu Nan)
3. Data Exploration-Artificial Intelligence and Machine Learning Development-Taking SPSS Modeler as an example (Boyan Culture)
4. Data Exploration (Shaped Sea)
5. Data Exploration (PEARSON, European Books Agency agent)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 平時成績(出席、參與及作業)平時成績(出席、參與及作業) Regular achievements (attendance, participation and work) |
30 | |
| 期中考期中考 Midterm exam |
25 | |
| 分組報告分組報告 Sub-group report |
20 | |
| 期末報告期末報告 Final report |
25 |
