本課程旨在培養學生掌握資料挖掘的核心技術，特別是在環境科學中的應用能力，幫助學生處理大規模環境數據，從數據收集、清洗、建模到分析與視覺化，全面理解資料挖掘流程。課程涵蓋環境數據的特性與處理方法，包括環境監測數據、氣象數據和水文數據等，並結合空間與時間序列分析，探索地理關係與趨勢模式。學生將學習統計、機器學習與人工智慧技術在污染預測、氣候變遷分析和生態管理中的應用，並透過專案導向學習解決實際環境問題，熟練操作如Python、GIS等工具。課程還強調數據視覺化與結果溝通，培養學生將技術成果轉化為政策建議的能力，從而成為具備環境科學與數據分析技能的跨領域專才，為解決當代環境挑戰提供創新方案。This course aims to cultivate students to master the core technology of data mining, especially their application capabilities in environmental science, helping students handle large-scale environmental data, from data collection, cleaning, modeling to analysis and visualization, and fully understand the data mining process. The course covers the characteristics and treatment methods of environmental data, including environmental monitoring data, atmosphere data and hydrological data, etc., and combines space and time sequence analysis to explore geographic relationships and trend patterns. Students will learn the application of statistics, machine learning and artificial intelligence in pollution prediction, climate change analysis and ecological management, and solve practical environment problems through project-oriented learning, and practice tools such as Python and GIS. The course also emphasizes data visualization and results communication, cultivates students' ability to transform technical achievements into policy advice, and thus becomes a cross-domain talent with environmental science and data analysis skills, providing innovative solutions to solve contemporary environmental challenges.
G. J. Myatt, W. P. Johnson, 2009. Making Sense of Data II - A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications. Wiley.
Robert Nisbet, John Elder,Gary Miner, 2009. Handbook of Statistical Analysis and Data Mining Applications. Elsevier Inc.
G. J. Myatt, W. P. Johnson, 2009. Making Sense of Data II - A Practical Guide to Data Visualization, Advanced Data Mining Methods, and Applications. Wiley.
Robert Nisbet, John Elder, Gary Miner, 2009. Handbook of Statistical Analysis and Data Mining Applications. Elsevier Inc.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 期末報告期末報告 Final report |
60 | 期末專題 |
| 上課討論上課討論 Class discussion |
20 | |
| 作業作業 Action |
20 |
