A Study on the Development of Courses Related to Artificial Intelligence and Mathematics in College General Mathematics

In order to develop courses related to artificial intelligence and mathematics, this study provides plans for the composition and operation of courses related to artificial intelligence and mathematics in college general mathematics by analyzing the mathematics curriculum, artificial intelligence and mathematics-related research, and selecting learning elements and contents. The content needed to deal with the principles of artificial intelligence in mathematics is mainly related to calculus, probability and statistics, and linear algebra. Such mathematical learning content is one of the functions of artificial intelligence. Since it is necessary for analysis and expression, neural networks, clustering, unsupervised learning, and optimization, these contents must be included in artificial intelligence and mathematics-related courses in college general mathematics. In addition, in courses related to artificial intelligence and mathematics, it is difficult for students to learn various topics such as linear algebra and multi-variable calculus, which are essential as basic mathematics for understanding machine learning, all in one semester. Thus, in this study, I propose that we divide the course into two subjects, <Artificial Intelligence Mathematics 1> and <Artificial Intelligence Mathematics 2>, so that college students can select and take the courses according to their abilities and needs. Lastly, while theory-oriented classes are essential for understanding the principles of artificial intelligence in artificial intelligence and mathematics-related courses, applied learning is also crucial. This includes learning the basics of Python, a widely used programming language, for data analysis, data organization, and preprocessing. Additionally, applying these skills in real-life projects involving data analysis, artificial intelligence, and deep learning is necessary for comprehensive education.