Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2026	360010	Data Science and Visualization	1	3.0	3	★	Li, Gordon Chun Yue	4BM3	2	0

Course Plan：

Instructor	Li, Gordon Chun Yue　Office Hours
Email	G.C.Li@ntut.edu.tw
Last Updated	2025-12-30 15:19:48
Course Objective	本課程透過 R 語言 介紹資料科學與資料視覺化。課程預設學生不具備 R 語言或資料程式設計的基礎經驗。課程內容聚焦於應用型資料科學技能，將帶領學生學習清理、探索、轉換和視覺化資料的方法。鑒於 AI 是未來程式設計與資料分析的趨勢，本課程鼓勵學生運用適當的 AI 工具來輔助學習與專案實作。學生將在練習和專案中，運用真實數據實踐這些方法。 This course introduces data science and data visualization through the R language. The course assumes no prior experience in R or data programming. Focusing on applied data science skills, students will be introduced to the methods to tidy, explore, transform, and visualize data. Recognizing that AI is the future of programming and data analysis, this course encourages students to utilize appropriate AI tools to assist with learning and project implementation. Students will practice them with real data in exercises and projects.
Course Schedule	週次 (Week) / 內容 (Content) I. Data Science 資料科學 (教科書/textbook: “R in Action” ) 1 和平紀念日 Peace Memorial Day 2 課程導論、軟體安裝 Introduction to the course, installation 3 R 語言基礎指令、套件 Basic R Commands, packages 4 資料選擇、資料格式 Data selection, Data formats 5 工作流程、比較分析 Workflows, comparisons 6 兒童節 Children’s Day 7 資料轉換：長型與寬型資料 (Data transformations: Long & Wide Data 8 函數、疊代 Functions, Iteration 9 期中考週 Midterm Week II. Visualization 資料視覺化 (教科書/textbook: “Data Visualization with R” ) 10 資料準備 Data Preparation (Ch. 1) 11 ggplot 簡介 Introduction to ggplot (Ch. 2) 12 單變量圖表、雙變量圖表 Univariate Graphs, Bivariate Graphs (Ch. 3-4) 13 多變量圖表 Multivariate Graphs (Ch. 5) 14 統計模型與圖表 Statistical Models and Graphs (Ch. 8) III. Analyzing Data 資料分析 15 迴歸 Regression 16 模型建構 Modeling 17 端午節 Dragon Boat Festival 18 期末週: 專案報告 Project Presentation
Evaluation and grading policy	32.5% Homework 32.5% Midterm 35.0% Final Project 100% Total
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Textbook: Data Visualization with R, Rob Kabacoff (free) Reference: R in Action: Data Analysis and Graphics with R, Robert Kabacoff Resources available in the library: R for data science : import, tidy, transform, visualize, and model data / Hadley Wickham, Garrett Grolemund. https://holding.lib.ntut.edu.tw/bookDetail/439156 R資料科學 / Hadley Wickham, Garrett Grolemund著 ; 黃銘偉譯 作者：韋克漢 (Wickham, Hadley) https://holding.lib.ntut.edu.tw/bookDetail/457346
The access to curricular consultation	傳LINE訊息或郵件給老師。 Send LINE message or email the instructor.
The course corresponds to the SDGs	SDG4：優質教育（Quality Education） SDG8：尊嚴就業與經濟發展（Decent Work and Economic Growth） SDG12：負責任的消費與生產（Responsible Consumption and Production）
Does the course incorporate AI	● 使用生成式AI作為教學過程的輔助工具（Use generative AI tools as an aid to the teaching process） ● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）
Note	As an EMI class, the class will be streamed and recorded via Google Meet to support diverse studying and reviewing habits and schedules. This format provides a clearer view of the shared screen, allows for automated closed captioning, and offers flexible timing for those who wish to revisit the lecture. 作為英語教學，課程同步提供 Google Meet 線上直播與錄影，以支援多樣化的學習與複習需求。此方式提供更清晰的共享螢幕畫面與自動字幕功能，更具備時間彈性，方便同學依照個人進度重複觀看或回顧教學內容。 Use of AI (vide coding) is encouraged in this course. 本課程鼓勵使用 AI 協助編碼與學習。