Welcome to the course webpage for Math 22A, Section 2. Here you will find some general info about the course. This is also the place to look for homework assignments, occasional course notes, practice exams, and other things that might interest you.

TA Information 22AL and other resources Textbook Exams and Grading Homework Assignments Material by Day Various Notes

Professor: Elena Fuchs

Office: MSB 3109

Email: efuchs at math dot ucdavis dot edu

Office hours: M 10:00-11:00AM, F 10:30AM-11:30AM.

Our TA's are Emily Meyers (eemeyer@ucdavis), Rui Okada (rokada@math.ucdavis), and Jianping Pan (jppan@math.ucdavis).

Emily Meyer: Fridays, 2-3PM in 3125 MSB

Rui Okada: Tuesdays, 1-2PM in 2127 MSB

Jianping Pan: Mondays, 2-3PM in 2129 MSB

Many of you are required to take Math 22AL and are taking it this quarter. This info sheet is a must read for those of you taking that course.

Everyone should also know that there are 22A workshops and daily drop-in tutoring available at the Student Academic Success Center. Please go to https://tutoring.ucdavis.edu/math for more information.

The textbook we'll be using is "Introduction to Linear Algebra" by G. Strang, 5th Edition. *If you have an earlier edition, it is your responsibility to figure out the differences to the 5th. Most relevant are the problems at the end of each section.*

Your grade for the course is determined as follows:

- 10% for weekly homework.
- 25% for Midterm 1 (January 31, in class)
- 25% for Midterm 2 (February 21, in class)
- 40% for the Final (March 18, 1-3PM)

**Homework** (along with occasional supplementary notes) will be posted here every Tuesday and will be due the following Tuesday. **I encourage you to submit your homework as a pdf on Canvas by scanning it using a scanner on campus or a scanner app on your phone.** If you do not do it this way, you can hand in a physical copy into one of our homework boxes in the Math Sciences Building on Tuesday by 4PM, located in a hallway just on the West side of the Calculus room. Solutions will be posted on Canvas every week.

**Our midterms** will be in class on **Friday, January 31st** and **Friday, February 21st**. More details about these exams will be announced in class and posted here closer to the dates.

**Our final exam** code is M. It will take place in our classroom on **Wednesday, March 18th, 1-3PM.**

We will cover most of the first six chapters from the textbook. For a detailed syllabus as suggested by the department of mathematics, please click here.

Our goal, in a nutshell, is to learn the basics of linear algebra: vectors, vector spaces, matrices, systems of linear equations, eigenvalues and eigenvectors. This topic is at the core of many facets of science and engineering, not to mention many fields in pure and applied mathematics.

The following is a rough outline of what we will be doing in lecture every day, along with the relevant sections in the book (note that the reading for a given lecture should be taken to mean the relevant section of the mentioned chapter). In reality, we may move faster or slower. It will be updated on a regular basis.

**1/6**: Introduction to the course; vectors and vector operations. Reading: section 1.1.**1/8**: Span of vectors, dot product, norms of vectors. Reading: Section 1.2.**1/10**: Norm, dot product, and orthogonality. Beginning matrices and systems of linear equations. Reading: Section 1.3.**1/13**: Matrix multiplication by vectors and systems of linear equations. Reading: Section 2.1.**1/15**: Augmented matrices and row operations to solve systems of linear equations. Reading: Sections 2.2.**1/17**: Matrix multiplication and inverses. Reading: Sections 2.3 and 2.4.**1/20**: Martin Luther King Jr. Day, no class**1/22**: Matrix inversion. Reading: Section 2.5.**1/24**: Matrix inversion continued. Reading: Section 2.5.**1/27**: Inverses of matrices corresponding to row operations. Reading: Section 2.6.**1/29**: Matrices as a product of lower and upper triangular matrices. Reading: Section 2.6.**1/31**: MIDTERM 1**2/3**: Going over Midterm 1, starting vector spaces. Reading: Section 3.1.**2/5**: Vector spaces, column space, null space. Reading: Section 3.1 and 3.2.**2/7**: Continuing column spaces and null spaces. Reading: Section 3.2 and 3.3.**2/10**: Reduced row echelon form and computing null spaces of matrices. Reading: Section 3.2.**2/12**: Rank of matrices and relation to null space. Reading: Section 3.2.**2/14**: Using null space to solve any system of linear equations. Reading: Section 3.3.**2/17**: University holiday, no class.**2/19**: Using null space to solve general systems of linear equations. Reading: Section 3.4.**2/21**: Midterm 2.**2/24**: Linear independence. Reading: Section 3.5.**2/26**: Bases of vector spaces. Reading: Section 3.5.**2/28**: Bases and calculuating bases of column space, null space, and row space. Reading: Section 3.6.