| 課程編碼 Course Code | 中文課程名稱 Course Name (Chinese) | 英文課程名稱 Course Name (English) | 總學分數 Credits | 總時數 Hours |
|---|---|---|---|---|
| 3725023 | 資料探勘與大數據分析 | Data Mining and Big Data Analytics | 3.0 | 3 |
| 中文概述 Chinese Description | 本課程旨在培養學生運用資料分析技術解決實務問題之能力。課程內容涵蓋資料型態與資料前處理，包括資料蒐集、清理、整合、轉換與特徵工程等資料準備技術；並介紹常用之資料探勘方法，如分類（Classification）、分群（Clustering）、關聯分析與預測模型建構。課程亦結合大數據分析概念與實務應用，培養學生對大量、多樣與高速資料之分析能力。此外，課程將探討自然語言處理（NLP）與文字探勘技術，包括斷詞、詞頻分析、情感分析、主題模型與文本分類等方法，應用於社群媒體、評論資料及文件分析。透過案例實作與分析工具操作，提升學生在人工智慧與資料科學領域之實務應用與研究能力。 | |||
| 英文概述 English Description | This course aims to develop students’ abilities to apply data analysis techniques to solve practical problems. The course covers data types and data preprocessing, including data collection, cleaning, integration, transformation,and feature engineering techniques for data preparation. It also introduces commonly used data mining methods, such as classification, clustering,association analysis, and predictive model construction. In addition, the course integrates big data analytics concepts with practical applications to cultivate students’ capabilities in analyzing large-scale, diverse, and high-velocity data.Furthermore, the course explores Natural Language Processing (NLP) and text mining techniques, including word segmentation, term frequency analysis, sentiment analysis, topic modeling, and text classification, with applications in social media, review data, and document analysis. Through case studies and hands-on analytical tool practices, students will enhance their practical | |||
備註：