Foundation of Artificial Intelligence

Course Purpose
The purpose of this course is for students to understand major research topics and their difficulties in the field of artificial intelligence, and to obtain the basic knowledge about representative methods for the topics.
Learning Goals
Students will acquire an understanding of basic techniques to cope with major problems of artificial intelligence.
Topic
Session 1Introduction
Session 2Issues of artificial intelligence (1): Search
Session 3Issues of artificial intelligence (2): Planning / Knowledge representation / Reasoning
Session 4Issues of artificial intelligence (3): Natural language processing
Session 5Issues of artificial intelligence (4): Speech recognition
Session 6Issues of artificial intelligence (5): Image processing
Session 7Pattern recognition and machine learning (1): Linear discriminant function
Session 8Pattern recognition and machine learning (2): Use of probability / Performance evaluation
Session 9Pattern recognition and machine learning (3): Support vector machine
Session 10Pattern recognition and machine learning (4): Neural network
Session 11Pattern recognition and machine learning (5): Distance-based method
Session 12Pattern recognition and machine learning (6): Clustering
Session 13Pattern recognition and machine learning (7): Decision tree / Ensemble learning
Session 14Total review
＊＊This content is based on April 1, 2025. For the latest syllabus information and details, please check the syllabus information inquiry page provided by the university.＊＊