教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
115-1	366989	機器學習	1	3.0	3	★	蔡偉和	AI雙聯專班	1	0	碩一修

教學大綱與進度：

教師姓名	蔡偉和　教師諮商時間(Office Hours)
Email	whtsai@ntut.edu.tw
最後更新時間	2026-06-29 13:43:12
課程大綱	This course introduces the concepts, techniques, and applications of machine learning. Topics mainly include Symbolists (e.g., Decision Tree), Connectionists (e.g., Artificial Neural Networks), Bayesians (e.g., Hidden Markov Model), Analogizers (e.g., kNN), and Evolutionaries (e.g., GA), Natural Language Processing and Speech Recognition. The lecture format will be a combination of slide presentation, chalk talk and computer demonstration. In addition to the theoretical study, students are guided to survey the related references, discuss and brainstorm by group, and conduct the practice projects, so that the capability of creativity and innovation can be developed during the course.
課程進度 (1-16週)	1. Introduction to Machine Learning (1hr) 2. Supervised Learning, e.g., Decision Tree, NB, kNN, SVM, Hidden Markov Model, and Artificial Neural Networks (9hr) 3. Unsupervised Learning, e.g., K-means Clustering, Hierarchical Clustering (9hr) 4. Machine Learning with WEKA (9hr) 5. Evolutionary Computing (8hr) 6. Natural Language Processing (5hr) 7. Speech Recognition (9hr) 8. Students' Project Presentation (4hr)
彈性學習 (17-18週)	類別 　 內容 　 時數 (小時) 　 學習成果 　 評量比例
評量方式與標準	Attendance and participation 30% Assignments 30% Oral presentation 40%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 1. "Data Mining - Practical Machine Learning Tools and Techniques (2nd Edition)" by Ian Witten and Eibe Frank, eBook ISBN: 9780080477022 (available in our school's library) 2. Terje Kristensen, Computational Intelligence, Evolutionary Computing and Evolutionary Clustering Algorithms. Sharjah, U.A.E.: Bentham Science Publishers. 2016 3. Dong Yu and Li Deng, Automatic Speech Recognition, A Deep Learning Approach. Springer, 2015
課程諮詢管道	email: whtsai@ntut.edu.tw
延伸教學與資源	● 混成學習 (Blended Learning) 課程結合實體授課與線上學習（同步視訊／非同步活動）。 Combines face-to-face instruction with online learning (including synchronous video sessions or asynchronous activities).
課程對應SDGs指標	SDG3：良好健康和福祉（Good Health and Well-being）
課程是否導入AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools） ● 簡單介紹AI的基本概念（Briefly introduce the basic concept of AI） ● 深入探討AI的原理與應用（Explore the principles and applications of AI in depth）
備註	上課時同步使用MS Teams視訊，詳細資訊將公告於北科i學園，或請洽 whtsai@ntut.edu.tw 詢問。