介紹數據分析的過程，從數據資料型態的介紹、數據處理過程，並將數據視覺化，以及數據的分類方法與相似性計算，介紹迴歸與預測的方法，分析分類準確度的定義與評估公式。提供互動平台，同學課後可以在互動平台找到資料與實際資料的解說，瞭解方法與透過線上程式可以執行與互動。讓學生透過網站可以直接在家練習與實做並提供問答。
Introduce the process of data analysis, from the introduction of data data types, data processing processes, and data visualization, as well as data classification methods and similarity calculation, introduce recitation and prediction methods, analyze the definition and evaluation formula of classification accuracy. Provide an interactive platform. After class, students can find explanations of data and actual data on the interactive platform, and understand methods and can be executed and interact through online programs. Let students practice and practice directly at home and provide questions through the website.
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
Introduction to Data Mining，Pang-Ning Tan，Michael Steinbach，Vipin Kumar，
Addison-Wesley，2006。
Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar,
Addison-Wesley, 2006.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 期中報告期中報告 Midterm Report |
20 | 期中報告 |
| 期末考期末考 Final exam |
20 | 期末考 |
| 期末報告期末報告 Final report |
50 | 期末繳交 |
| 平時成績平時成績 Regular achievements |
10 | 出席、作業、演習課 |
