## Course Summary

This is a first course in linear algebra. It is truly surprising how ubiquitous linear algebra is throughout math and sciences: from cryptography to graph theory, from machine learning to research mathematics. Whether you are an aspiring computer scientist, mathematician, physicist, biologist or engineer, the techniques we will learn in this class are a fundamental component of your studies. Topics include solving linear systems of equations, span and linear independence of vectors, linear transformations, inverses, subspaces, change of basis, the determinant function, eigenvalues and eigenvectors, and diagonalization.

## Information

**Instructor:** Josh Southerland

**Office Hours:** 4:00-6:00 Tuesday

**Office:** Padelford (PDL), C-552

**Contact:** j s o u t h e r AT u w . e d u

Additional help is available outside of class and office hours at CLUE. Visit their website to find out more about drop-in hours and dedicated M308 days.

## Homework & Webassign

For homework, you will need to use Webassign. Professor Taggart how generously typed up instructions for how to use Webassign. You can find them here. When you log into Webassign, use this link (or google "uw Webassign" to get this page).

## Exams

**Midterm 1:** Friday, October 18

**Midterm 2:** Wednesday, November 13

**Final Exam:** Thursday, December 12

## Lecture Notes

- Lecture 1: 1.1
- Lecture 2: 1.2
- Lecture 3: 2.1
- Lecture 4: 2.2
- Lecture 5: 2.3
- Lecture 6: 3.1
- Lecture 7: 3.2
- Lecture 8: 3.3
- Lecture 9: 4.1
- Lecture 10: 4.2
- Lecture 11: 4.3
- Lecture 12: 4.4
- Lecture 13: 5.1, 5.2

## Exam Archives

Midterm 1: Archive 1, Archive 2 (You may ignore all problems asking about linear transformations.)

Midterm 2: Archive 1, Archive 2 (You may ignore questions asking you to change the basis, compute a determinant, or compute eigen-anything.)

Final Exam: Archive 1, Archive 2 (You may ignore problems that ask about orthogonality and least squares regression. You do not need to worry about complex-valued eigenvalues, you only need to know how to work with real-valued eigenvalues.)

## Other Materials

- Chapter 1 Conceptual Problems
- Chapter 2 Conceptual Problems
- Chapter 3 Conceptual Problems
- Chapter 4 Conceptual Problems
- Chapter 5 Conceptual Problems
- Chapter 2 Videos: Vectors, Span and Linear Independence
- Chapter 3 Videos: Linear Transformations and Matrices, Matrix Multiplication as Composition, 3D Linear Transformations
- Chapter 4 Videos: Inverse Matrices, Column Space and Null Space, Nonsquare matrices as Transformations between Dimensions, Change of Basis
- Chapter 5 Video: The Determinant
- Chapter 6 Video: Eigenvalues and Eigenvectors

## Course Schedule

Week | Monday | Tuesday | Wednesday | Thursday | Friday |
---|---|---|---|---|---|

1, 9/23 | Lecture: 1.1 | No HW | Lecture: 1.1, 1.2 | ||

2, 9/30 | Lecture: 1.2 | HW: 1.1 | Lecture: 1.2, 2.1 | HW: 1.2 | Lecture: 2.1 |

3, 10/7 | Lecture: 2.2 | HW: 2.1 | Lecture: 2.3 | HW: 2.2 | Lecture: 2.3 |

4, 10/14 | Review Day | HW: 2.3 | Lecture: 3.1 | No HW | Midterm 1 |

5, 10/21 | Lecture: 3.1, 3.2 | HW: 3.1 | Lecture: 3.2 | HW: 3.2 (Sun) | Lecture: 3.2, 3.3 |

6, 10/28 | Lecture: 3.3 | HW: 3.3 | Lecture: 4.1 | HW: 4.1 | Lecture: 4.2 |

7, 11/4 | Lecture: 4.3 | HW: 4.2, 4.3 | Review | Lecture: 4.4 | |

8, 11/11 | Holiday | No HW | Midterm 2 | HW: 4.4 | Lecture: 5.1, 5.2 |

9, 11/18 | Lecture: 5.1, 5.2 | HW: 5.1, 5.2 | Lecture: 6.1 | No HW | Lecture: 6.1 |

10, 11/25 | Lecture: 6.2 | HW: 6.1 | Lecture: 6.2, (6.3) | Holiday | Holiday |

11, 12/12 | Review | HW: 6.2 | Review | No HW | Review |

12, 12/9 | Final Exam 12/12/19 |