本課程整合經濟學、統計學與電腦科學三大領域，旨在引導學生認識數據分析與經濟建模之核心理論與實務技能。課程內容涵蓋資料分析流程之各個關鍵環節，包括資料前處理（如資料清理與整理）、分析方法與建模技術（如各類演算法之原理與應用）、模型訓練與驗證之最佳化技巧，以及模型建構完成後之預測能力評估與準確度檢測。此外，課程亦將介紹文字資料探勘與分析方法，協助學生處理非結構化資料。同時，課程將融入程式設計教學，並搭配實際案例進行操作練習，培養學生學用合一的能力。最終，期使學生能以經濟學的觀點解讀分析結果，並據以進行決策判斷。
修習本課程後，學生將能夠：
(1)掌握數據分析與模型建構之核心概念與發展脈絡；
(2)具備基本程式設計能力，以支援資料處理與分析工作；
(3)能依研究目的選用適當的分析方法與演算工具進行實證分析；
(4)從經濟學觀點詮釋數據結果，並提出具洞見的分析與決策建議，培養成為具備跨域能力之數據分析人才。

This course integrates the three major fields of economics, statistics and computer science, aiming to guide students to understand the core theoretical and practical skills of data analysis and economic modeling. The course content covers all key aspects of the data analysis process, including data pre-processing (such as data cleaning and sorting), analysis methods and modeling techniques (such as the principles and applications of various algorithms), optimization techniques for model training and verification, and prediction ability evaluation and accuracy testing after the model is constructed. In addition, the course will also introduce text data exploration and analysis methods to help students process unstructured data. At the same time, the course will be integrated into programming teaching and combined with actual cases for operational exercises to cultivate students' ability to integrate learning and application. Ultimately, students are expected to be able to interpret analytical results from an economic perspective and make decision-making judgments based on them.
After taking this course, students will be able to:
(1) Master the core concepts and development context of data analysis and model construction;
(2) Have basic programming skills to support data processing and analysis work;
(3) Be able to select appropriate analytical methods and calculation tools for empirical analysis according to the research purpose;
(4) Interpret data results from an economic perspective and provide insightful analysis and decision-making suggestions to cultivate data analysis talents with cross-domain capabilities.

本課程結合經濟學、統計學與電腦科學，帶領學生學習與瞭解數據分析與經濟建模的核心知識與基本技能。課程設計包括數據分析所需要的資料處理與建模流程，從數據清理與整理的前置作業、數據分析與建模所需要的各種演算法與應用、模型訓練與驗證的最佳化技術，以及建模後的測試準確性檢驗作一系列的介紹。其次，進一步瞭解文字型態資料的探勘技術與分析方法。同時，課程將會教導學生使用編程，並搭配個案實際操作練習。最後，學生能夠以經濟學的視角來解釋數據分析結果來作決策。

This course combines economics, statistics and computer science to lead students to learn and understand the core knowledge and basic skills of data analysis and economic modeling. The course design includes a series of introductions to the data processing and modeling processes required for data analysis, including pre-work on data cleaning and sorting, various algorithms and applications required for data analysis and modeling, optimization techniques for model training and verification, and post-modelling test accuracy inspection. Secondly, learn more about the exploration technology and analysis methods of text-type data. At the same time, the course will teach students how to use programming and combine it with practical case studies. Finally, students can interpret data analysis results from an economic perspective to make decisions.

無指定教科書，自行編製講義。

There is no designated textbook and you will prepare your own handouts.