Artificial Intelligence的摘要

Artificial Intelligence

教師: 戴敏育

國立臺北大學

2023/06/05~2023/08/18

14小時/11週 (報名結束)

攻專業 EMI Professional Studies

摘要

Artificial intelligence is a technology that thinks and acts like humans. AI is a rapidly evolving field with significant technical advancements and innovative applications across various industries, shaping the way we live and work. As AI continues to develop, it has the potential to revolutionize many aspects of our society and transform industries in unprecedented ways.
Dr. Min-Yuh Day has --- practical experience in artificial intelligence and has published more papers in high impact journal. Take this big opportunity and build your own practice in Artificial intelligence application. This course helps you to know about AI from the zero and later to hero in AI.

#英語授課 #人工智慧

課程目標

1.Understand the fundamental concepts and research issues of Artificial Intelligence.

2.Equip with Hands-on practices of Artificial Intelligence.

3.Conduct information systems research in the context of Artificial Intelligence

4.Exploring new knowledge in information technology, system development and application.

授課教師

戴敏育博士

Dr. Min-Yuh Day is an Associate Professor in the Graduate Institute of Information Management at National Taipei University, Taiwan.

Research Interest:

His current research interests include electronic commerce, financial technology, artificial intelligence, big data analytics, data mining and text mining, social media marketing, information systems evaluation, question answering systems, and biomedical informatics.

Experience:

He was an Associate Professor in the Department of Information Management at Tamkang University, Taiwan.

He was a Postdoctoral Fellow in the Intelligent Agent Systems Lab, Institute of Information Science, Academia Sinica, Taiwan.

課程進度表

單元 1:Introduction to Artificial Intelligence

單元 2:Artificial Intelligence and Intelligent Agents

單元 3:Problem Solving

單元 4:Knowledge, Reasoning and Knowledge Representation; Uncertain Knowledge and Reasoning

單元 5:Midterm exam

單元 6:Machine Learning: Supervised and Unsupervised Learning

單元 7:The Theory of Learning and Ensemble Learning

單元 8:Deep Learning for Natural Language Processing

單元 9:Computer Vision and Robotics

單元 10:Philosophy and Ethics of AI and the Future of AI

單元 11:Final exam

評分標準

影片瀏覽Class Participation：佔總成績 70 %

期中考Midterm exam：佔總成績 15 %

期末考Final exam：佔總成績 15 %

通過標準

課程及格標準:60分滿分：100分

建議參考書目

Required Texts: Stuart Russell and Peter Norvig (2020),Artificial Intelligence: A Modern Approach,4th Edition, Pearson.

Reference Books: Aurélien Géron (2019), Hands-On Machine Learning with Scikit-Learn, Kera’s, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, 2nd Edition, O’Reilly Media.

Steven D'Ascoli (2022), Artificial Intelligence and Deep Learning with Python: Every Line of Code Explained for Readers New to AI and New to Python, independently published.

Nithin Buduma, Nikhil Buduma, Joe Papa (2022), Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms, 2nd Edition, ‎O'Reilly Media