Course Syllabus

Course Information：

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

Fall Semester
Year 2026 363034 Introduction to Artificial Intelligence and Programming Languages (1) 1 3.0 3 ▲ FANG-CHIH TIEN
Hsieh-Ching Chen 4IEM1B 0 0 計中電腦教室

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	363034	Introduction to Artificial Intelligence and Programming Languages (1)	1	3.0	3	▲	FANG-CHIH TIEN Hsieh-Ching Chen	4IEM1B	0	0	計中電腦教室

Course Plan：

Instructor FANG-CHIH TIEN　Office Hours

Email fctien@ntut.edu.tw

Last Updated 2026-06-16 20:50:35

Course Objective 本課程之目的在訓練大學部學生於撰寫程式之能力，程式語言(一)以Python 為實踐主體，課程內容包含: 複習Operators and Expression、流程控制 (while, for, if-elif-else)、函式(function)、module、data structure；並學習 input/output、OOP (Class 概念)、及 exception；並將介紹廣泛使用之標準程式庫，包括: sys、datetime、os、random、argparse、numpy、pandas、matplotlib、pillow、pyqt、scipy， scikit-learn、opencv-python、request、Selenium、beautifulsoup4 等；並將配合學期之project，訓練同學團隊合作及系統開法之經驗。 The objective of this course is to cultivate the programming ability for undergraduates. Python is the language used in this course since its simplicity and widely applicable. The content of this course includes: reviewing operators and expression, flow control, functions, module, data structure, and extensively learning input/output, class (OOP), and exception. Besides, this course will introduce the commonly used packages, such as os, numpy, sys, pandas, matplotlib, pillow, pyqt, etc. There will be a term project to let student experience team-working and system design and management.

Course Schedule Week 1: Introduction to Python and python installation Week 2: Operators and Expression Week 3: 流程控制 I (Logic control) Week 4: 流程控制 II (Logic control) Week 5: 函式(Function) Week 6: module and function Week 7: datta structure: tuple、list、dictionary Week 8: input/output (file) Week 9: Test #1 Week 10: Class I Week 11: Class II Week 12: Problem-Based Learning: Topic I – Database, openxl Week 13: Problem-Based Learning: Topic II – Image Processing Week 14: Problem-Based Learning: Topic III – Webserver Week 15: Problem-Based Learning: Topic IV – GUI (PyQt) Week 16: Problem-Based Learning: Topic IV – GUI (Statistics) Week 17: Final Week 18: Project Demo

Evaluation and grading policy 作業及課堂練習 10% 期中考x2 15% x2 = 30% 期末考 20% x2 = 40% 小考 (多次，每次 1~2%) 25%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:No
1. byte-of-python (電子書網路費版中/English) 2. 個人教材 (PPT) + Video 3. 相關網頁 4. 個人 YouTube

The access to curricular consultation 每週二下午諮詢時間 14:00~16:00

Expanding teaching and resources ● 數位科技融入 (Digital Technology Integration)
運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。
Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.

The course corresponds to the SDGs 無（None）

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
Google meet 上課網址:https://meet.google.com/tqp-izpk-xfh

本課主要為工管系同學所設計之課程，外系同學建議不要選修此課程

Instructor	FANG-CHIH TIEN　Office Hours
Email	fctien@ntut.edu.tw
Last Updated	2026-06-16 20:50:35
Course Objective	本課程之目的在訓練大學部學生於撰寫程式之能力，程式語言(一)以Python 為實踐主體，課程內容包含: 複習Operators and Expression、流程控制 (while, for, if-elif-else)、函式(function)、module、data structure；並學習 input/output、OOP (Class 概念)、及 exception；並將介紹廣泛使用之標準程式庫，包括: sys、datetime、os、random、argparse、numpy、pandas、matplotlib、pillow、pyqt、scipy， scikit-learn、opencv-python、request、Selenium、beautifulsoup4 等；並將配合學期之project，訓練同學團隊合作及系統開法之經驗。 The objective of this course is to cultivate the programming ability for undergraduates. Python is the language used in this course since its simplicity and widely applicable. The content of this course includes: reviewing operators and expression, flow control, functions, module, data structure, and extensively learning input/output, class (OOP), and exception. Besides, this course will introduce the commonly used packages, such as os, numpy, sys, pandas, matplotlib, pillow, pyqt, etc. There will be a term project to let student experience team-working and system design and management.
Course Schedule	Week 1: Introduction to Python and python installation Week 2: Operators and Expression Week 3: 流程控制 I (Logic control) Week 4: 流程控制 II (Logic control) Week 5: 函式(Function) Week 6: module and function Week 7: datta structure: tuple、list、dictionary Week 8: input/output (file) Week 9: Test #1 Week 10: Class I Week 11: Class II Week 12: Problem-Based Learning: Topic I – Database, openxl Week 13: Problem-Based Learning: Topic II – Image Processing Week 14: Problem-Based Learning: Topic III – Webserver Week 15: Problem-Based Learning: Topic IV – GUI (PyQt) Week 16: Problem-Based Learning: Topic IV – GUI (Statistics) Week 17: Final Week 18: Project Demo
Evaluation and grading policy	作業及課堂練習 10% 期中考x2 15% x2 = 30% 期末考 20% x2 = 40% 小考 (多次，每次 1~2%) 25%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No 1. byte-of-python (電子書網路費版中/English) 2. 個人教材 (PPT) + Video 3. 相關網頁 4. 個人 YouTube
The access to curricular consultation	每週二下午諮詢時間 14:00~16:00
Expanding teaching and resources	● 數位科技融入 (Digital Technology Integration) 運用生成式AI、VR/AR、IoT、IRS等新興科技輔助教學與評量。 Utilizes emerging technologies such as Generative AI, VR/AR, IoT, and IRS (Interactive Response Systems) to facilitate teaching and assessment.
The course corresponds to the SDGs	無（None）
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	Google meet 上課網址:https://meet.google.com/tqp-izpk-xfh 本課主要為工管系同學所設計之課程，外系同學建議不要選修此課程