Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2025 345293 Linear Algebra 1 3.0 3 ★ Hsiao-Chi Li 4EE1A 45 0 預選40人

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2025	345293	Linear Algebra	1	3.0	3	★	Hsiao-Chi Li	4EE1A	45	0	預選40人

Course Plan：

Instructor Hsiao-Chi Li　Office Hours

Email hcli@mail.ntut.edu.tw

Last Updated 2024-12-17 13:55:29

Course Objective This course covers fundamentals of mathematics in matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, and similarity.

Course Schedule Week 1: Overview; Systems of Linear Equations Week 2-3: Row Reduction and Echelon Forms; Vector and Matrix Equations Week 4: Solution Sets of Linear Systems Week 5-6: Linear Independence Week 7-8: Matrix Algebra 01: Basic Operations, invertible theorem Week 9: Midterm Week 10: Matrix Algebra 02: Matrix Partition, Factorization Week 11: Linear Transformation and Characteristics of Invertible Matrices Week 12-13: Determinants; Vector Spaces and Coordinate Systems; Change of Basis Week 14: Eigenvectors and Eigenvalues; The Characteristic Equation Week 15: Diagonalization; Orthogonal Sets; Orthogonal Projections Week 16: Principal Component Analysis Week 17: Machine Learning and Linear Models Week 18: Final

Evaluation and grading policy Grading - Homework 15% Quiz 15% Midterm 30% Final 30% Attendance 10% Policy on Copying - Copying is not acceptable. Do your own work.

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Textbook - D. Lay, Linear Algebra and its Applications, 6th Edition, Pearson, 2021. Reference - S.H. Friedberg, A.J. Insel, and L.E. Spence, Linear Algebra, 4th Edition, Pearson, 2002. G. Strang, Introduction to Linear Algebra, 4th Edition, Wellesley-Cambridge Press, 2009. K.M. Hoffman, and R. Kunze, Linear Algebra, 2nd Edition, Pearson, 1971.

The access to curricular consultation E-mail: hcli@mail.ntut.edu.tw

The course corresponds to the SDGs 無（None）

Does the course incorporate AI

Note
　

Instructor	Hsiao-Chi Li　Office Hours
Email	hcli@mail.ntut.edu.tw
Last Updated	2024-12-17 13:55:29
Course Objective	This course covers fundamentals of mathematics in matrix theory and linear algebra. Emphasis is given to topics that will be useful in other disciplines, including systems of equations, vector spaces, determinants, eigenvalues, and similarity.
Course Schedule	Week 1: Overview; Systems of Linear Equations Week 2-3: Row Reduction and Echelon Forms; Vector and Matrix Equations Week 4: Solution Sets of Linear Systems Week 5-6: Linear Independence Week 7-8: Matrix Algebra 01: Basic Operations, invertible theorem Week 9: Midterm Week 10: Matrix Algebra 02: Matrix Partition, Factorization Week 11: Linear Transformation and Characteristics of Invertible Matrices Week 12-13: Determinants; Vector Spaces and Coordinate Systems; Change of Basis Week 14: Eigenvectors and Eigenvalues; The Characteristic Equation Week 15: Diagonalization; Orthogonal Sets; Orthogonal Projections Week 16: Principal Component Analysis Week 17: Machine Learning and Linear Models Week 18: Final
Evaluation and grading policy	Grading - Homework 15% Quiz 15% Midterm 30% Final 30% Attendance 10% Policy on Copying - Copying is not acceptable. Do your own work.
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Textbook - D. Lay, Linear Algebra and its Applications, 6th Edition, Pearson, 2021. Reference - S.H. Friedberg, A.J. Insel, and L.E. Spence, Linear Algebra, 4th Edition, Pearson, 2002. G. Strang, Introduction to Linear Algebra, 4th Edition, Wellesley-Cambridge Press, 2009. K.M. Hoffman, and R. Kunze, Linear Algebra, 2nd Edition, Pearson, 1971.
The access to curricular consultation	E-mail: hcli@mail.ntut.edu.tw
The course corresponds to the SDGs	無（None）
Does the course incorporate AI
Note