| Homework | 39% |
| Exams | 40% |
| Final | 21% |
Grading is according to the following fixed scale.
| ≥90% | ≥85% | ≥80% | ≥75% | ≥70% | ≥65% | ≥60% | ≥55% | ≥50% | ≥45% | ≥40% | else |
|---|---|---|---|---|---|---|---|---|---|---|---|
| A | A- | B+ | B | B- | C+ | C | C- | D+ | D | D- | E |
| Date | Topic | Textbook | HW Due |
|---|---|---|---|
| 8/21 | Introduction | ||
| 8/22 | Systems of linear equations | 1.1 | |
| 8/23 | Row reduction and echelon forms | 1.2 | |
| 8/25 | How to solve a linear system | ||
| 8/28 | Vector equations | 1.3 | #1 |
| 8/29 | The matrix equation Ax=b | 1.4 | |
| 8/30 | Solution sets of linear systems | 1.5 | |
| 9/1 | Applications of linear systems | 1.6 | |
| 9/4 | NO CLASS | ||
| 9/5 | Linear independence | 1.7 | #2 |
| 9/6 | Linear transforms and their matrix | 1.8-1.9 | |
| 9/8 | Matrix operations | 2.1 | |
| 9/11 | The inverse of a matrix | 2.2 | #3 |
| 9/12 | Review | ||
| 9/13 | Exam on chapter 1 | ||
| 9/15 | Characterizations of invertible matrices | 2.3 | |
| 9/18 | Partitioned matrices | 2.4 | #4 |
| 9/19 | Matrix factorizations | 2.5 | |
| 9/20 | Subspaces of Rn | 2.8 | |
| 9/22 | Dimension and rank | 2.9 | |
| 9/25 | Review | #5 | |
| 9/26 | Exam on chapter 2 | ||
| 9/27 | Determinants | 3.1 | |
| 9/29 | Properties of determinants | 3.2 | |
| 10/2 | Cramer’s rule | 3.3 | #6 |
| 10/3 | Vector spaces and subspaces | 4.1 | |
| 10/4 | Null spaces etc. | 4.2 | |
| 10/6 | Basis and dimension | 4.3, 4.5 | |
| 10/16 | Coordinate systems | 4.4 | #7 |
| 10/17 | Change of basis | 4.6 | |
| 10/18 | Difference equations | 4.8 | |
| 10/20 | Eigenvectors and eigenvalues | 5.1 | |
| 10/23 | The characteristic equation | 5.2 | #8 |
| 10/24 | Diagonalization | 5.3 | |
| 10/25 | More on eigenvalues and eigenvectors | 5.4-5.5 | |
| 10/27 | Review | ||
| 10/30 | Review | #9 | |
| 10/31 | Exam on chapters 3-5 | ||
| 11/1 | The Gershgorin theorem | ||
| 11/3 | Inner product, length, orthogonality | 6.1 | |
| 11/6 | Orthogonal sets | 6.2 | #10 |
| 11/7 | Orthogonal projections | 6.3 | |
| 11/8 | The Gram-Schmidt process | 6.4 | |
| 11/10 | Least-squares problems | 6.5 | |
| 11/13 | Machine learning and linear models | 6.6 | #11 |
| 11/14 | Inner product spaces | 6.7 | |
| 11/15 | Applications of inner product spaces | 6.8 | |
| 11/17 | Diagonalization of symmetric matrices | 7.1 | |
| 11/20 | Quadratic forms | 7.2 | #12 |
| 11/21 | Constrained optimization | 7.3 | |
| 11/22 | Singular value decomposition | 7.4 | |
| 11/24 | NO CLASS | ||
| 11/27 | More on singular value decomposition | #13 | |
| 11/28 | Review | ||
| 11/29 | Exam on chapters 6-7 | ||
| 12/1 | The QR factorization | ||
| 12/4 | Review | #14 | |
| 12/5 | Review | ||
| 12/6 | Review |
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