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 (x-hour) |
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 (x-hour) |
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 |
Gram-Schmidt 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 |
|
Wrap-up |
Bjoern Muetzel
Last updated October 24, 2019