This course aims to introduce the fundamental theory of linear algebra and its applications in the field of agronomy. It is designed for students with limited mathematical background who wish to apply linear algebra to practical problems. The course covers essential concepts such as matrices and systems of linear equations, vector spaces, and eigenvalues and eigenvectors. Through the use of applied examples and case studies, students will learn how to use linear algebraic methods to analyze and solve real-world problems.

1. Master the fundamental concepts and theory of linear algebra, including matrix operations, solving systems of linear equations, and vector spaces. 2. Understand the meaning of eigenvalues and eigenvectors and their applications in practical problems. 3. Become familiar with the use of linear algebra tools in data processing and analysis, such as principal component analysis (PCA). 4. Strengthen students’ data analysis skills and build a solid foundation for further study in statistical analysis and machine learning.

待補

Pre-class study hours: 2 hours; post-class study hours: 4 hours.

待補

待補