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。
在完成此課程的學習，學生將
(1) 瞭解數據分析與模型建構的核心知識與發展趨勢；
(2) 具備編寫程式語言的技能；
(3) 選擇並應用合適的分析方法和演算工具；
(4) 能夠在更廣泛的經濟背景下構建問題，並且提供與該背景相關的獨特見解，成為一位數據分析師的角色。This course combines economics, disciplines and computer science, and leads students to learn and understand the core knowledge and basic skills of data analysis and economic modeling. Course design includes data processing and modeling processes required for data analysis, from the pre-operation of data cleaning and sorting, various algorithms and applications required for data analysis and modeling, model training and verification optimization techniques, as well as The test accuracy test after modeling is introduced in a series of introductions. Secondly, further understand the exploration technology and analysis methods of text-shaped data. At the same time, the course will teach students to use the program and be accompanied by a case-based practice. Finally, students can explain the results of data analysis from an economic perspective to make decisions.
After completing the course learning, students will
(1) Understand the core knowledge and development trends of data analysis and model construction;
(2) Have skills in writing programming languages;
(3) Select and apply appropriate analytical methods and calculation tools;
(4) Be able to construct problems in a broader economic context and provide unique solutions to the background, becoming the role of a data analyst.
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, disciplines and computer science, and leads students to learn and understand the core knowledge and basic skills of data analysis and economic modeling. Course design includes data processing and modeling processes required for data analysis, from the pre-operation of data cleaning and sorting, various algorithms and applications required for data analysis and modeling, model training and verification optimization techniques, as well as The test accuracy test after modeling is introduced in a series of introductions. Secondly, further understand the exploration technology and analysis methods of text-shaped data. At the same time, the course will teach students to use the program and be accompanied by a case-based practice. Finally, students can explain the results of data analysis from an economic perspective to make decisions.
無指定教科書，自行編製講義。
No designated textbooks, self-editing speech.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 課堂參與課堂參與 Class Participation |
30 | 含課堂表現、報告、出席，以及自主學習。 |
| 作業作業 Action |
20 | |
| 期中實作考試期中實作考試 Midterm practice exam |
25 | |
| 期末實作考試期末實作考試 Final practice exam |
25 |
