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 359221 Data Analysis and Processing 1 3.0 3 ★ CHEN WEN-HUI GAT 10 0 　

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2026	359221	Data Analysis and Processing	1	3.0	3	★	CHEN WEN-HUI	GAT	10	0

Course Plan：

Instructor CHEN WEN-HUI　Office Hours

Email whchen@ntut.edu.tw

Last Updated 2025-12-18 20:09:35

Course Objective 本課程教授資料分析之實務應用。課程內容教授程式設計搭配實務應用實例。提供學生學習資料分析與處理的基本技巧，包括數據模型、視覺化處理及實例應用之探討。為提升學習成效，本課程與「電機自動化設計軟體」（課號：359438）課程相互結合，以強化學生在自動化科技領域中對資料分析的理解與應用。本課程內容重點放在程式設計與資料分析教學。透過系統化的訓練，學生將能在自動化科技領域中更有效掌握資料分析方法，並培養獨立應用與技術創新的能力。

Course Schedule Week 1: Holiday (228 Memorial Day) Week 2: Course Outlines & Logistics Week 3: Introduction to Data Science Week 4: Math & Statistics Week 5-7: Modern AI & Machine Learning (I) Week 8-10: Modern AI & Machine Learning (II) Week 11: Midterm Review Week 12-14: Programming & Industrial Applications in Data Analysis(I) Week 15-17: Programming & Industrial Applications in Data Analysis (II) Week 18: Project Presentation and Discussion

Evaluation and grading policy 1. In-class Exercises & Assignments: 70% 2. Final Project: 30%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Lecture Slides

The access to curricular consultation 綜科館605

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）
SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
SDG10：減少不平等（Reduced Inequalities）

Does the course incorporate AI ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）

Note
　

Instructor	CHEN WEN-HUI　Office Hours
Email	whchen@ntut.edu.tw
Last Updated	2025-12-18 20:09:35
Course Objective	本課程教授資料分析之實務應用。課程內容教授程式設計搭配實務應用實例。提供學生學習資料分析與處理的基本技巧，包括數據模型、視覺化處理及實例應用之探討。為提升學習成效，本課程與「電機自動化設計軟體」（課號：359438）課程相互結合，以強化學生在自動化科技領域中對資料分析的理解與應用。本課程內容重點放在程式設計與資料分析教學。透過系統化的訓練，學生將能在自動化科技領域中更有效掌握資料分析方法，並培養獨立應用與技術創新的能力。
Course Schedule	Week 1: Holiday (228 Memorial Day) Week 2: Course Outlines & Logistics Week 3: Introduction to Data Science Week 4: Math & Statistics Week 5-7: Modern AI & Machine Learning (I) Week 8-10: Modern AI & Machine Learning (II) Week 11: Midterm Review Week 12-14: Programming & Industrial Applications in Data Analysis(I) Week 15-17: Programming & Industrial Applications in Data Analysis (II) Week 18: Project Presentation and Discussion
Evaluation and grading policy	1. In-class Exercises & Assignments: 70% 2. Final Project: 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Lecture Slides
The access to curricular consultation	綜科館605
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） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure） SDG10：減少不平等（Reduced Inequalities）
Does the course incorporate AI	● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI）
Note