Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Fall Semester
Year 2025 352362 Data Science and Visualization 1 3.0 3 ★ Li, Gordon Chun Yue GBM 27 0 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2025	352362	Data Science and Visualization	1	3.0	3	★	Li, Gordon Chun Yue	GBM	27	0

Course Plan：

Instructor Li, Gordon Chun Yue　Office Hours

Email G.C.Li@ntut.edu.tw

Last Updated 2025-08-28 15:59:56

Course Objective 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. Students will practice them with real data in exercises and projects.

Course Schedule Week. Dates: Content I.Data Science 1. Introduction to the course, installation 2. Basic R Commands, packages 3. Data selection, Data formats 4. Workflows, comparisons 5. Data transformations 6. Functions, Iteration II. Visualization 7. Data Preparation (Ch. 1) 8. Introduction to ggplot (Ch. 2) 9. Exam Week 10. Univariate Graphs (Ch. 3), Bivariate Graphs (Ch. 4) 11. Multivariate Graphs (Ch. 5), Maps (Ch. 6) 13. Time Series Graphs (Ch. 7), Statistical Models and Graphs (Ch. 8) III. Practice 13. Project Time 14. Introduction to R libraries and modeling 15. Project Presentation 16. Project Presentation (for those who haven't presented) 17. Exam Week

Evaluation and grading policy 32.5% Homework and Quizzes 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 Send LINE message or email the instructor.

Expanding teaching and resources

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）

Note
　

Instructor	Li, Gordon Chun Yue　Office Hours
Email	G.C.Li@ntut.edu.tw
Last Updated	2025-08-28 15:59:56
Course Objective	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. Students will practice them with real data in exercises and projects.
Course Schedule	Week. Dates: Content I.Data Science 1. Introduction to the course, installation 2. Basic R Commands, packages 3. Data selection, Data formats 4. Workflows, comparisons 5. Data transformations 6. Functions, Iteration II. Visualization 7. Data Preparation (Ch. 1) 8. Introduction to ggplot (Ch. 2) 9. Exam Week 10. Univariate Graphs (Ch. 3), Bivariate Graphs (Ch. 4) 11. Multivariate Graphs (Ch. 5), Maps (Ch. 6) 13. Time Series Graphs (Ch. 7), Statistical Models and Graphs (Ch. 8) III. Practice 13. Project Time 14. Introduction to R libraries and modeling 15. Project Presentation 16. Project Presentation (for those who haven't presented) 17. Exam Week
Evaluation and grading policy	32.5% Homework and Quizzes 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	Send LINE message or email the instructor.
Expanding teaching and resources
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）
Note