Syllabus
Week 
Date 
Chapter 
Brief Description 
1 
9/16 
1.1 
Systems of Linear Equations 

9/18 
No class 
BM in Providence, RI 

9/20 
1.2 
Row Reduction and Echelon Form 
2 
9/23 
1.3 
Vectors 

9/25 
1.4 & 1.5 
The Matrix Equation Ax=b, Solutions of Linear Systems 

9/26 (xhour) 
1.6 
Applications of Linear Systems 

9/27 
1.7 
Linear Independence 
3 
9/30 
1.8 
Introduction to Linear Transformations 

10/2 
1.9 
The Matrix of a Linear Transformation 

10/3 (xhour) 
2.1 
Matrix Operations 

10/4 
2.2 
The Inverse of a Matrix 
4 
10/7 
2.3 
Characterizations of Invertible Matrices 

10/9 
3.1 & 3.2 
Determinants and their Properties 

10/11 
4.1 
Vector Spaces and Subspaces 
5 
10/14 
4.2 
Null Spaces, Column Spaces and Linear Transformations 

10/16 
4.3 
Linear Independence and Bases 

10/18 
4.4 
Coordinate Systems 
6 
10/21 
4.5 
Dimension of a Vector Space 

10/23 
4.6 
Rank of a Matrix 

10/25 
4.7 
Change of Basis 
7 
10/28 
6.1 & 6.2 
Inner product, Length and Orthogonality, Orthogonal sets 

10/30 
6.3 
Orthogonal Projections 

11/1 
6.4 
GramSchmidt Process 
8 
11/4 
6.5 
Least Square Method and Data Fitting 

11/6 
5.1 
Eigenvectors and Eigenvalues 

11/8 
5.2 
The Characteristic Equation 
9 
11/11 
5.3 
Diagonalization 

11/13 
Lecture 
Markov Chains and Google's Page Rank Algorithm 

11/15 

Presentation of Projects 
10 
11/18 

Wrapup 
Bjoern Muetzel
Last updated October 24, 2019