I4210 教學大綱表

教學大綱表 (112學年度第2學期)

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課程名稱 Course Title	(中文) AI實務專題 (英文) Ai Practice Topic			開課單位 Departments	資訊工程學系
				課程代碼 Course No.	I4210
授課教師 Instructor	謝禎冏謝尚琳
學分數 Credit	2.0	必/選修 core required/optional	選修	開課年級 Level	大四
先修科目或先備能力(Course Pre-requisites)：Neural network, Deep learning, Artificial Intelligence
課程概述與目標(Course Overview and Goals)：This course is the whole course of AI course. First, it explains the practical examples of the application of AI technology in data exploration, natural language, computer vision, image synthesis and so on. Then the course will lead students to design project topics, will learn the theory of AI applied to daily life or industrial automation, the development of applied value AI system, and through class discussion and sharing to confirm its value, and gradually make this final project to demonstrate students' creativity. Learning goals: 1. AI development tools. 2. AI practice example 3. AI project design and implementation 4. Project Management and collaboration 5. Final project presentation. This course is one of the EMI courses which are taught all in English.
教科書(Textbook)	Self-collected material
參考教材(Reference)	IEEE/ACM conference or journal papers, OpenCV/Keras official document website, Python 技術者們，實踐! (施威銘研究室)

課程大綱 Syllabus			學生學習目標 Learning Objectives	單元學習活動 Learning Activities	學習成效評量 Evaluation	備註 Notes
序 No.	單元主題 Unit topic	內容綱要 Content summary	學生學習目標 Learning Objectives	單元學習活動 Learning Activities	學習成效評量 Evaluation	備註 Notes
1	1. Course requirement	Develop AI projects in teams (<=8 groups)	Learning in teams
2	2. AI SDK/platform	Python on Anaconda + Jupyter + Keras	Using tools to develop AI related projects
3	3. Tools and libraries	Numpy, Pandas, Scikit	Learn how to use these packages and understand the syntax
4	4. Process of an AI project	Mnist/Cifar-10/Hand gesture recognition	Learn the life cycle of AI development
5	5. Collection of data	(AIdea) https://aidea-web.tw/	Learn how to get the dataset
6	6. Understanding the problem or invited speech	Group discussion or invited speech	Know what kind of development in industry
7	7. Web Crawler + Multi-thread	Data collection – image as an example	Know how to get data from internet
8	8. Fake news classifier	Practice I	Do a sample project by oneself.
9	9. Mid-term report	Project proposal(Motivation, related works, and proposed method)	Midterm
10	10. Bit coin best selling point	Practice II	Learn how to develop a project
11	11. Traffic sign classification	Practice III	Learn how to develop a project
12	12. Intrusion detection	Practice IV	Learn how to develop different AI projects
13	13. Invited speech I	(徐紹鐘) AI related topics I	Know what AI application is being used in industry
14	14. Invited speech II	(何文楨) AI related topics II	AI researches in industry
15	15. Students report by group	Data Collection	Collect their own dataset
16	16. Students report by group	AI models and training results	Train their own model
17	17. Students report by group	System integration	Build a complete project
18	18. Final report by group	Demo videos & final reports	Final

彈性教學週活動規劃

序 No.	實施期間 Period	實施方式 Content	教學說明 Teaching instructions	彈性教學評量方式 Evaluation	備註 Notes
1	起:2024-06-11 迄:2024-06-21	5.小專題 Project	實作期末專題	Demo+簡報

教學要點概述：
1.自編教材 Handout by Instructor：
■ 1-1.簡報 Slids
□ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
□ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
□ 3.教科書作者提供 Textbook

成績考核 Performance Evaluation：期末考：30% 期中考：30% 專題：10% 彈性教學：10% 作業：20%

教學資源(Teaching Resources)：
□ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)
課程網站(Website)：網路大學
扣考規定：http://eboard.ttu.edu.tw/ttuwebpost/showcontent-news.php?id=504