Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2025	346402	Cross-Disciplinary Project Implementation of Artificial Intelligence	1	3.0	3	★	Wen-Yi Lee Chung, Chien-Ping	管理學院(大)	26	0

Course Plan：

Instructor	Chung, Chien-Ping　Office Hours
Email	thomas6311@mail.ntut.edu.tw
Last Updated	2025-02-04 23:20:11
Course Objective	本課程整合Open AI雲端服務資源，運用問題分析能力進行實作與相關應用，以企業出題學生解題PBL模式導入人工智慧跨域專題實作，目的在幫助學生瞭解如何運用人工智慧技術來解決現實世界中的問題。 本課程透過導入人工智慧在企業管理和決策、金融、數據分析、智慧製造等領域等應用案例，並以通用人工智慧跨域應用學習模式來跨域應用至數據分析、智慧運算、智慧製造及物流、商情預測、經營管理、金融等領域。透過本課程的修習，學生將獲得實際的跨學科專題實作能力，掌握人工智慧技術的應用和發展趨勢，養成專業職能和研發實力，並培育具有創業與創新精神人才，了解產業在數位轉型中，所面臨的困難與挑戰。 This course integrates resources from OpenAI cloud services, utilizing problem analysis skills for practical implementation and related applications. It introduces an industry-proposed, student-solved Project-Based Learning (PBL) model into the interdisciplinary project implementation of artificial intelligence. The aim is to help students understand how to apply AI technology to solve real-world problems. Through the introduction of artificial intelligence applications in enterprise management and decision-making, finance, data analysis, and smart manufacturing, the course enables students to gain practical interdisciplinary project implementation skills. This course also helps students understand the difficulties and challenges faced by industries in digital transformation.
Course Schedule	第1週 Introduction/The Fundamentals of Machine Learning 第2週 End-to-End Machine Learning Project 第3週 End-to-End Machine Learning Project 第4週 Classification 第5週 Training Models 第6週 Support Vector Machines 第7週 Decision Trees 第8週 Ensemble Learning and Random Forests 第9週 Midterm Exam 第10週 Deep learning related issues 第11週 Deep learning related issues 第12週 Industrial Applications and Development Strategies of Generative AI 第13週 Applications of Artificial Intelligence in Smart Finance 第14週 Generative AI Marketing Strategies and Corporate Applications 第15週 Fundamentals and Extended Applications of Large Language Models 第16週 Practical Implementation of Open-Source Large Language Models 第17週 Project-Based AI Implementation Group Report (I) 第18週 Project-Based AI Implementation Group Report (II)
Evaluation and grading policy	Homework 20%(Assignments are designed to reinforce the concepts discussed in lectures) Midterm 30% (The midterm exam is designed to assess students' understanding of foundational topics, particularly those related to prediction) Final report 40% (The final report is a comprehensive integration for cross-disciplinary AI projects) Class participation 10% (Active engagement in class)
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 3rd O'Reilly Media 自編教材/投影片
The access to curricular consultation	課堂中宣布 本課程透過導入人工智慧在企業管理和決策、金融、數據分析、智慧製造等領域等應用案例，並以通用人工智慧跨域應用學習模式來跨域應用至數據分析、智慧運算、智慧製造及物流、商情預測、經營管理、金融等領域。透過本課程的修習，學生將獲得實際的跨學科專題實作能力，掌握人工智慧技術的應用和發展趨勢，養成專業職能和研發實力，並培育具有創業與創新精神人才，了解產業在數位轉型中，所面臨的困難與挑戰。
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）
Does the course incorporate AI
Note	本課程整合Open AI雲端服務資源，運用問題分析能力進行實作與相關應用，以企業出題學生解題PBL模式導入人工智慧跨域專題實作，目的在幫助學生瞭解如何運用人工智慧技術來解決現實世界中的問題。 本課程著重於實作人工智慧模型於Open AI雲端服務資源。相較於傳統撰寫Keras、PyTorch等框架於本機端，本課程更偏向於使用現有框架於雲端計算。