巨量數據分析與機器學習

臺北科技大學 114-2 學期課程，課號 356433。

課程大綱

本課程旨在提供社會科學領域背景的碩博士研究生熟悉並掌握機器學習的分析技術，並能將其運用在分析巨量的結構(數字)或非結構數據資料(文字、圖像、社群關係)。課程內容將以python作為數據分析的軟體，並介紹如何使用網絡爬蟲以及API服務擷取並整理所需要的目標數據，此外將介紹包括知識圖譜的繪製、肢體動作圖像辨識、自然語言處理的技術以及應用等。由於本課程需要大量的程式編寫作業，並須有一定的程式與統計基礎，學生須先修過教育統計學和校務研究，始可修習本課程。另曾修習多變量分析課程者尤佳。 This course is tailored for graduate students majoring in social sciences, equipping them with the skills to proficiently employ machine learning in their big data analysis endeavors. The applications of machine learning encompass both structured and unstructured data analysis. The course will include instruction on Python programming. Topics covered will encompass web scraping, data acquisition via API services, science mapping, motion detection, and natural language processing. This course places a high demand on both programming skills and a solid foundation in statistics. Prerequisite courses for enrollment in this course include educational statistics and institutional research. And taking multivariate analysis before this course is highly recommend although it is not requirement.

課程進度

第一週：學期課程介紹與程式環境設定 第二週：認知與腦神經科學關係 第三週：腦神經科學訊號收集與數據分析 第四週：肢體動作與運動科學 第五週：肢體動作訊號收集與數據分析 第六週：專題實作：閱讀習慣或動作習慣的辨識 第七週：地理空間資訊系統與全球圖層界接 第八週：臺灣人口結構特徵圖繪製 第九週：公共基礎設施可近性：以醫療院所為例 第十週：代理人模型介紹 第十一週：代理人模型與地理空間資訊系統整合分析 第十二週：專題實作：理想醫療院所區位的選定 第十三週：數位文本與自然語言處理 第十四週：應用生成式AI標記文本資料 第十五週：鄉土地方誌的深度解析 第十六週：期末報告：優化高齡個人生活品質 第十七週：期末報告：優化高齡社會資源配置 第十八週：課程回顧 Week 1: Course Overview and Programming Environment Setup Week 2: The Relationship between Cognition and Neuroscience Week 3: Neuroscience Signal Acquisition and Data Analysis Week 4: Human Movement and Motor Science Week 5: Motion Signal Acquisition and Data Analysis Week 6: Project-Based Practice: Identifying Reading Habits or Movement Patterns Week 7: Geographic Information Systems (GIS) and Global Map Layer Integration Week 8: Mapping Taiwan’s Population Structure Week 9: Accessibility of Public Infrastructure: The Case of Healthcare Facilities Week 10: Introduction to Agent-Based Modeling Week 11: Integrated Analysis of Agent-Based Models and Geographic Information Systems Week 12: Project-Based Practice: Identifying Optimal Locations for Healthcare Facilities Week 13: Digital Texts and Natural Language Processing Week 14: Applying Generative AI to Text Data Annotation Week 15: In-Depth Analysis of Local Gazetteers and Community Histories Week 16: Final Project Presentation: Optimizing Quality of Life for Older Adults Week 17: Final Project Presentation: Optimizing the Allocation of Social Resources for an Aging Society Week 18: Course Review

評量方式

Assessment and Grading Criteria Class Participation and Attendance: 30% Project-Based Assignments: 30% Final Project Report: 40%

教材

【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 Instructional Materials: Instructor-Developed Python Materials