教學大綱表 (112學年度 第3學期)
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課程名稱
Course Title		 (中文) 線性代數
(英文) Linear Algebra 		開課單位
Departments		 資訊工程學系
課程代碼
Course No.		 I2610
授課教師
Instructor		 蔡佳勝
學分數
Credit		 3.0 必/選修
core required/optional		 必修 開課年級
Level		 大一
先修科目或先備能力(Course Pre-requisites)：
課程概述與目標(Course Overview and Goals)：Able to handle vectors and matrices.
Understand the concepts of vector spaces.
Solving linear systems
understand the concepts of eigenvectors/eigenvalues
教科書(Textbook) Gareth Williams, "Linear Algebra with Applications,"
參考教材(Reference)
課程大綱 Syllabus 學生學習目標
Learning Objectives		 單元學習活動
Learning Activities		 學習成效評量
Evaluation		 備註
Notes
序
No.		 單元主題
Unit topic		 內容綱要
Content summary
1 Linear Equations 1. Introduction to linear systems
2. Gauss-Jordan elimination
3. Matrix algebra 		1. Introduction to linear systems
2. Gauss-Jordan elimination
3. Matrix algebra		 學習如何利用矩陣解線性方程  
2 Linear Equations 1. Introduction to linear systems
2. Gauss-Jordan elimination
3. Matrix algebra 		1. Introduction to linear systems
2. Gauss-Jordan elimination
3. Matrix algebra		 學習如何利用矩陣解線性方程  
3 Linear Equations 1. Introduction to linear systems
2. Gauss-Jordan elimination
3. Matrix algebra 		1. Introduction to linear systems
2. Gauss-Jordan elimination
3. Matrix algebra		 學習如何利用矩陣解線性方程  
4 Linear Transformations 1. Linear transformations
2. The inverse of Linear transformations 		1. Linear transformations
2. The inverse of Linear transformations		 學習線性轉換的要領  
5 Linear Transformations 1. Linear transformations
2. The inverse of Linear transformations 		1. Linear transformations
2. The inverse of Linear transformations		 學習線性轉換的要領  
6 Linear Transformations 1. Linear transformations
2. The inverse of Linear transformations 		1. Linear transformations
2. The inverse of Linear transformations		 學習線性轉換的要領  
7 Subspaces and Dimensions 1. Image and kernel of a linear transformation
2. Bases and linear independence
3. The dimensions 		1. Image and kernel of a linear transformation
2. Bases and linear independence
3. The dimensions		 學習子空間與基底的概念  
8 Subspaces and Dimensions 1. Image and kernel of a linear transformation
2. Bases and linear independence
3. The dimensions 		1. Image and kernel of a linear transformation
2. Bases and linear independence
3. The dimensions		 學習子空間與基底的概念  
9 Subspaces and Dimensions 1. Image and kernel of a linear transformation
2. Bases and linear independence
3. The dimensions 		1. Image and kernel of a linear transformation
2. Bases and linear independence
3. The dimensions		 學習子空間與基底的概念  
10 Midterm examination examination 測試期中學習成效  
11 Orthogonality and Least Squares 1. Orthogonal projection
2. Gram-Schmidt process and QR factorization
3. Least squares and data fitting 		1. Orthogonal projection
2. Gram-Schmidt process and QR factorization
3. Least squares and data fitting		 學習正交投影與QR分解之概念與應用  
12 Orthogonality and Least Squares 1. Orthogonal projection
2. Gram-Schmidt process and QR factorization
3. Least squares and data fitting 		1. Orthogonal projection
2. Gram-Schmidt process and QR factorization
3. Least squares and data fitting		 學習正交投影與QR分解之概念與應用  
13 Determinants 1. Introduction to determinants
Cramer's rule 		1. Introduction to determinants
Cramer's rule		 學習行列式值概念與應用  
14 Determinants 1. Introduction to determinants
Cramer's rule 		1. Introduction to determinants
Cramer's rule		 學習行列式值概念與應用  
15 Eigenvalues and Eigenvectors 1. Finding the eigenvalues of a matrix
2. Finding the eigenvectors of a matrix
3. Diagonalization
4. Stability 		1. Finding the eigenvalues of a matrix
2. Finding the eigenvectors of a matrix
3. Diagonalization
4. Stability		 學習特徵值與特徵向量之求法及其應用  
16 Eigenvalues and Eigenvectors 1. Finding the eigenvalues of a matrix
2. Finding the eigenvectors of a matrix
3. Diagonalization
4. Stability 		1. Finding the eigenvalues of a matrix
2. Finding the eigenvectors of a matrix
3. Diagonalization
4. Stability		 學習特徵值與特徵向量之求法及其應用  
17 Eigenvalues and Eigenvectors 1. Finding the eigenvalues of a matrix
2. Finding the eigenvectors of a matrix
3. Diagonalization
4. Stability 		1. Finding the eigenvalues of a matrix
2. Finding the eigenvectors of a matrix
3. Diagonalization
4. Stability		 學習特徵值與特徵向量之求法及其應用  
18 Final exam examination examination 測試期末學習成效  


教學要點概述：
1.自編教材 Handout by Instructor：
□ 1-1.簡報 Slids
□ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
□ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
□ 3.教科書作者提供 Textbook

成績考核 Performance Evaluation：

教學資源(Teaching Resources)：
□ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)
教學相關配合事項：none
扣考規定：http://eboard.ttu.edu.tw/ttuwebpost/showcontent-news.php?id=504