教學大綱與進度
課程基本資料:
學年期
課號
課程名稱
階段
學分
時數
修
教師
班級
人
撤
備註
112-2
332559
大數據與人工智能應用系統設計
1
3.0
3
★
林佑達
創新AI學位學程
8
2
教室地點先鋒大樓一樓城市科學實驗室
教學大綱與進度:
教師姓名
林佑達
Email
Roylin918@gmail.com
最後更新時間
2024-02-23 11:01:50
課程大綱
當代都市議題經常為跨領域、開放性的複雜問題,在資料蒐集與分析上,需要整合地理空間、時間的維度;在分析與對策上,須平衡公部門、私部門、民眾等多重利害關係者的,是一門相當複雜但重要的學問。本課程從真實的都市議題出發,教導學生掌握地理空間資訊、資料處理與分析、資訊視覺化、策略論述等綜合能力,培養學生對於都市複雜議題的觀察與剖析,進而對真實環境提出洞見與創意。本課程以分組操作為主,每組需挑選各自關切的都市議題,進行相關分析作業。內容包括:都數據獲取與處理、資訊視覺化、地理運算、都市建模、策略形塑,並包含一次期中報告,與一次期末成果報告。 Contemporary urban issues are often complex, interdisciplinary, and open-ended. In terms of data collection and analysis, they require the integration of geographical, spatial, and temporal dimensions. In analysis and strategy formulation, it is necessary to balance the interests of multiple stakeholders such as the public sector, private sector, and the general public. It is a highly complex yet crucial field of study. This course starts from real urban issues, teaching students to master skills in geographic information, data processing and analysis, information visualization, strategic discourse, and other comprehensive abilities. It aims to cultivate students' observation and analysis of complex urban issues, thereby enabling them to propose insights and creativity for real environments. This course primarily involves group work, where each group selects urban issues of their concern for relevant analysis tasks. The content includes data acquisition and processing, information visualization, geographic computation, urban modeling, and strategic shaping. It also includes one midterm report and one final project report.
課程進度
(1-16週)
第一週:都市數據與應用概論 第二週:放假 第三~四週:都市數據處理 第五~七週:空間運算與資料視覺化 第八週:期中分組報告 第九~十三週:都市數據建模 第十四~十七週:都市策略形塑 第十八週:期末分組報告 Week 1: Introduction to Urban Data and Applications Week 2: Holiday Week 3-4: Urban Data Processing Week 5-7: Spatial Computation and Data Visualization Week 8: Midterm Group Presentation Week 9-13: Urban Data Modeling Week 14-17: Urban Strategy Formulation Week 18: Final Group Presentation
評量方式與標準
個人課程參與 30%: 平時上課出席率、討論參與度、每週進度等綜合評比。 分組期中成果 30%: 各組期中簡報的成果總體評比,同一組每個成員評分相同。 分組期末成果 40%: 各組期中簡報的成果總體評比,同一組每個成員評分相同。 Individual Course Participation 30%: Comprehensive assessment of regular class attendance, participation in discussions, weekly progress, etc. Group Midterm Results 30%: Overall evaluation of each group's midterm presentation results, with the same score given to each member within the same group. Group Final Results 40%: Overall evaluation of each group's final presentation results, with the same score given to each member within the same group.
使用教材、參考書目或其他
【遵守智慧財產權觀念,請使用正版教科書,不得使用非法影印教科書】
使用外文原文書:否
必備軟體:Excel, QGIS, R-studio, Tableau Public 選用軟體/語言:Python, R, Power BI 數據來源:國內外開放資料 Required Software: Excel, QGIS, R-studio, Tableau Public Optional Software/Languages: Python, R, Power BI Data Sources: Domestic and international open data
課程諮詢管道
授課老師:roylin918@gmail.com
助教一名。
延伸教學與資源
課程對應SDGs指標
課程是否導入AI
備註