隨著人工智慧和機器學習技術的快速發展和應用，這些技術正在深深地改變公共領域的行政管理方式和政策制定過程。在這門課程中，將討論如何利用機器學習（Machine Learning, ML）的技術來解決公共事務的問題。課程將涵蓋機器學習的基本原理，包含如何設計、實施和評估機器學習模型。並將探討這些技術在公共政策、公共服務和行政決策等公共事務領域的具體應用。
這門課將透過案例研究和實際專案，讓學生理解如何在公共事務中應用機器學習。學生將學習使用二種常見的工具和平台設計和執行他們自己的機器學習模型，以解決真實世界的公共事務問題。
With the rapid development and application of artificial intelligence and machine learning technologies, these technologies are profoundly changing the administrative management methods and policy-making processes in the public sector. In this course, we will discuss how to use machine learning (ML) technology to solve public affairs problems. The course will cover the basic principles of machine learning, including how to design, implement, and evaluate machine learning models. And will explore the specific applications of these technologies in public affairs fields such as public policy, public services and administrative decision-making.
This course will allow students to understand how to apply machine learning in public affairs through case studies and practical projects. Students will learn to design and execute their own machine learning models using two common tools and platforms to solve real-world public affairs problems.
教師自備講義。
Teachers prepare their own handouts.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 專案實作一--以Python程式語言(書面報告)專案實作一--以Python程式語言(書面報告) Project Implementation 1 - Using Python Programming Language (Written Report) |
30 | 以自行尋找取得之公共事務相關資料進行實作。 |
| 專案實作二--以KNIME分析平台(書面報告)專案實作二--以KNIME分析平台(書面報告) Project implementation two--using KNIME analysis platform (written report) |
30 | 以自行尋找取得之公共事務相關資料進行實作。 |
| 作業與出席作業與出席 Homework and Attendance |
20 | |
| 任一專案實作之口頭報告任一專案實作之口頭報告 Oral report on the implementation of any project |
20 |
