Math 18: Linear Algebra

Lectures A00 (Anzaldo), B00 (Carfagnini), C00 (Bach), and D00 (Brust)

About this Course

Welcome to Math 18! This is a one quarter course on linear algebra. Linear algebra is, in many ways, the backbone of mathematics, engineering, and science. It plays a central role in computation at all levels, including the most basic: the device you're using to read this webpage, at its core, is doing nothing but linear algebra all day long. Linear algebra is fundamental to statistics, foundational to physical sciences, and is the ground floor of calculus. (Calculus is about approximating structures with simpler linear structures; linear algebra is the theory of those simpler linear structures.) This course will also introduce you, gently, to the world of mathematical thinking and rigor. It may well be the most important course you ever take!

Course Information

Modality: During Fall 2022,

All lectures will be delivered in-person, and some will also be podcasted.
All discussion sections will be in-person, with the exception of Sections A15, A16, A17, A18, A21, A22, A23, A24, C01, C02, C03, C04, and C05 which will meet remotely via Zoom at the scheduled times.
The midterms and final will be administered in-person, at the announced times, with no exceptions.
Masking is still required in indoor classrooms and instructional settings, which includes lecture, discussion, office hours, and exams.

Canvas: The LMS (learning management system) for this course is Canvas. The Canvas page for this course is combined for all lectures (A00, B00, C00, D00). Canvas will be used in various ways throughout the course, but this course webpage is the main portal for the course.

Piazza: We will use Piazza, an online discussion board, as a principal communication tool. It will allow you to post messages and answer posts made by your fellow students, about course content, homework, exams, etc. The instructors and TAs will also monitor and post to Piazza regularly. You can access Piazza from your Canvas site, or directly.
Gradescope: We will use Gradescope to grade your MATLAB homework, midterms, and final exam in this course. You will be able to view your graded assignments and assessments in Gradescope once they are graded and published. You can access Gradescope via Canvas.

Lecture Recordings: Recordings of lectures that are podcasted will be available in the Media Gallery on Canvas as well as on the UCSD podcast website.

Textbook: The required textbook for this course is

Linear Algebra and its Applications w/ MyMathLab/eBook (6th Edition), by David C. Lay, Steven R. Lay, and Judi J. McDonald.
This is the textbook available at the UC San Diego bookstore. If you choose to purchase it elsewhere, be aware that you need MyLab access, which is included with the bookstore version of the textbook but not with all versions. Note: you may also forego the physical textbook and just purchase a MyLab access code directly from the publisher Pearson the first time you login to MyLab (through Canvas); this includes access to the ebook version of the textbook. You are encouraged to take advantage of Pearson's "temporary access without payment for 14 days," which will let you do the MyLab homework and access the eText for free for two weeks, in case there is a possibility that you will drop the course. You will have the option to purchase access after the two weeks is over, and your homework scores during the trial period will be saved.

Discussion Sections are a required component of this course. You must attend your scheduled discussion section each week (on time) to receive full credit in the class. The discussion sections will involve community building and active learning, and will play a key role in your success at mastering linear algebra.

MyLab Homework: Weekly homework will be assigned through MyLab, the online Pearson homework system. You will find the assignments through the MyLab link in Canvas. See the syllabus for more details.

MATLAB: One component of our coursework is a series of MATLAB assignments, and a MATLAB quiz at the end. You will submit your MATLAB work through Gradescope. All information relevant to the MATLAB component of Math 18 can be found here.

Exams: In this course there will be two midterm exams and one final exam. Dates, times, and locations are posted below. Note that there will be no make-up dates for the midterms or final. There will be no alternate times for the final exam; if you cannot take the final exam at its scheduled time, you should not enroll in this class.

Instructional Staff

Name	Role	Office	Office hours (see Canvas for Zoom links)	Email
Leesa Anzaldo	Lead Instructor	APM 1240	Remote: Mon 7pm-8pm, Wed 7pm-8pm, Sun 12pm-1pm In-person: Wed 9am-10am	lbanzaldo@ucsd.edu
Marco Carfagnini	Instructor	APM 6305	In-person: Wednesday 1:20pm-3:20pm in APM 6303	mcarfagnini@ucsd.edu
Quang Bach	Instructor	APM 1250	Remote: TuTh 3pm-4pm, Saturday 10:30am-12:30pm	qtbach@ucsd.edu
Johannes Brust	Instructor	APM 1111	Remote: Mon and Fri 3:30pm-4:40pm In-person: Wed 3:30pm-4:30pm	jjbrust@ucsd.edu
Cameron Cinel	Lead TA		Remote: Tuesday 2-3 PM, Wednesday 2-4 PM	ccinel@ucsd.edu
Jon Stephens	Lead TA	HSS 5005	In-person: Tuesday/Thursday 12:30pm-2pm	jcstephens@ucsd.edu
Vitor Borges da Silva	TA	HSS 5044	In-person: Tuesday 3:30pm-5:30pm	vborgesdasilva@ucsd.edu
Runqiu Xu	TA	HSS 4037	In-person: Monday 4-6pm	r4xu@ucsd.edu
Haoyu Zhang	TA	HSS 4047	In-person: Monday/Wednesday 1pm-3pm	haz053@ucsd.edu
Yuchen Wu	TA	APM 6414	In-person: Thursday 3:30pm-5:30pm	yuw181@ucsd.edu
Minyoung Jeong	TA	APM 5712	In-person: Tuesday 5pm-7pm	m1jeong@ucsd.edu
Haotian Qu	TA		Remote: Tuesday 6pm-8pm	haqu@ucsd.edu
Nathan Wenger	TA	HSS 5029	Remote: Monday/Thursday 1:30-2:30	nwenger@ucsd.edu
Nicholas Zhao	TA	HSS 4084	Hybrid: Friday 10am-2pm	nizhao@ucsd.edu
Toren D'Nelly-Warady	TA	APM 2313	In-person: Wednesday, Thursday 10am-11am in HSS 5012	tdnellywarady@ucsd.edu
Lizzy Coda	TA	HSS 5012	In-person: Monday 5pm-7pm	ecoda@ucsd.edu
Shuncheng Yuan	TA	APM 5412	Remote: Monday 6:00-8:00pm	syuan@ucsd.edu
Sutanay Bhattacharya	TA	APM 6414	In-person: Wednesday 2pm-4pm	subhattacharya@ucsd.edu
Itai Maimon	Senior MATLAB TA			matlabta@math.ucsd.edu

We will also have support from the Academic Achievement Hub's Supplemental Instruction. SI Leaders will be embedded in some of our discussion sections to facilitate active learning, and there will also be separate SI Sessions run through the Teaching + Learning Commons.

Please note: Piazza should be your first stop for any course-related communication with the instructional staff. We ask that when you have a question about the class that might be relevant to other students, you post your question on Piazza instead of emailing us. That way, everyone can benefit from the response. Please only email your instructor/TA in the case of an urgent private matter (relevant to your enrollment in the course).

Class Meetings

In the following scheduled meeting times, physical locations are listed where relevant. Zoom meeting coordinates can be found in Canvas.

Lecture A00 Meetings	Date	Time	Location
Lecture A00 (Instructor: Anzaldo)	MWF	11:00am - 11:50am	JEANN AUD
Discussion A01 (TA: Borges da Silva)	Tu	10:00am - 10:50am	HSS 4025
Discussion A02 (TA: Borges da Silva)	Tu	11:00am - 11:50am	HSS 4025
Discussion A03 (TA: Xu)	Tu	12:00pm - 12:50pm	HSS 4025
Discussion A04 (TA: Xu)	Tu	1:00pm - 1:50pm	HSS 4025
Discussion A05 (TA: Xu)	Tu	2:00pm - 2:50pm	HSS 4025
Discussion A06 (TA: Xu)	Tu	3:00pm - 3:50pm	HSS 4025
Discussion A07 (TA: Zhang)	Tu	4:00pm - 4:50pm	HSS 4025
Discussion A08 (TA: Zhang)	Tu	5:00pm - 5:50pm	HSS 4025
Discussion A09 (TA: Zhang)	Tu	6:00pm - 6:50pm	HSS 4025
Discussion A10 (TA: Zhang)	Tu	7:00pm - 7:50pm	HSS 4025
Discussion A11 (TA: Wu)	Tu	8:00am - 8:50am	PCYNH 120
Discussion A12 (TA: Wu)	Tu	9:00am - 9:50am	PCYNH 120
Discussion A13 (TA: Jeong)	Tu	12:00pm - 12:50pm	CENTR 217A
Discussion A14 (TA: Jeong)	Tu	1:00pm - 1:50pm	CENTR 217A
Discussion A15 (TA: Qu)	Tu	2:00pm - 2:50pm	Remote
Discussion A16 (TA: Qu)	Tu	3:00pm - 3:50pm	Remote
Discussion A17 (TA: Qu)	Tu	4:00pm - 4:50pm	Remote
Discussion A18 (TA: Qu)	Tu	5:00pm - 5:50pm	Remote
Discussion A21 (TA: Wenger)	Tu	12:00pm - 12:50pm	Remote
Discussion A22 (TA: Wenger)	Tu	1:00pm - 1:50pm	Remote
Discussion A23 (TA: Wenger)	Tu	2:00pm - 2:50pm	Remote
Discussion A24 (TA: Wenger)	Tu	3:00pm - 3:50pm	Remote

Lecture B00 Meetings	Date	Time	Location
Lecture B00 (Instructor: Carfagnini)	MWF	12:00pm - 12:50pm	LEDDN AUD
Discussion B01 (TA: Zhao, SI: Henstridge)	Tu	2:00pm - 2:50pm	WLH 2113
Discussion B02 (TA: Zhao, SIs: Shukla, Wang, Venerio)	Tu	3:00pm - 3:50pm	WLH 2113
Discussion B03 (TA: Zhao, SIs: Shukla, Wang, Venerio)	Tu	4:00pm - 4:50pm	WLH 2113
Discussion B04 (TA: Zhao, SIs: Shukla, Wang)	Tu	5:00pm - 5:50pm	WLH 2208
Discussion B05 (TA: D'Nelly-Warady, SIs: Shukla, Venerio)	Tu	6:00pm - 6:50pm	SOLIS 111
Discussion B06 (TA: D'Nelly-Warady, SIs: Shukla, Venerio)	Tu	7:00pm - 7:50pm	SOLIS 111

Lecture C00 Meetings	Date	Time	Location
Lecture C00 (Instructor: Bach)	MWF	2:00pm - 2:50pm	WLH 2005
Discussion C01 (TA: Coda, SIs: Puneet, Nguyen)	Tu	9:00am - 9:50am	Remote
Discussion C02 (TA: Coda, SIs: Puneet, Nguyen, Patil)	Tu	10:00am - 10:50am	Remote
Discussion C03 (TA: Yuan, SIs: Henstridge, Nguyen, Gupta)	Tu	11:00am - 11:50am	Remote
Discussion C04 (TA: Yuan, SIs: Henstridge, Puneet, Gupta)	Tu	12:00pm - 12:50pm	Remote
Discussion C05 (TA: Cinel, SIs: Henstridge, Patil)	Tu	1:00pm - 1:50pm	Remote

Lecture D00 Meetings	Date	Time	Location
Lecture D00 (Instructor: Brust)	MWF	5:00pm - 5:50pm	LEDDN AUD
Discussion D01 (TA: Bhattacharya, SIs: Patil, Hu)	Tu	9:00am - 9:50am	RWAC 0115
Discussion D02 (TA: Bhattacharya, SI: Hu)	Tu	10:00am - 10:50am	RWAC 0115
Discussion D03 (TA: Borges da Silva, SIs: Hu, Wu)	Tu	8:00am - 8:50am	HSS 4025
Discussion D04 (TA: Borges da Silva, SI: Wu)	Tu	9:00am - 9:50am	HSS 4025
Discussion D05 (TA: Stephens, SI: Wu)	Tu	10:00am - 10:50am	PCYNH 120

Exam Info

	Date	Time	Location
Midterm Exam 1	Friday, October 21	7:00pm - 8:50pm	A00: PETER 108 and 110 B00: LEDDN AUD C00: MOS 0113 D00: CTL 0125
Midterm Exam 2	Thursday, November 10	8:00pm - 9:50pm	A00: PETER 108 and 110 B00: MOS 0113 C00: SOLIS 107 D00: CTL 0125
Final Exam	Saturday, December 3	7:00pm - 9:59pm	TBA

Calendar of Course Content

The following calendar is subject to revision during the term. The section references are only a guide; our pace may vary from it somewhat.

Week	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday
0	Sep 19	Sep 20	Sep 21	Sep 22	Sep 23 1.1 Systems of Linear Equations	Sep 24
1	Sep 26 1.2 Row Reduction and Echelon Forms	Sep 27 Discussion	Sep 28 1.3 Vector Equations	Sep 29	Sep 30 1.4 The Matrix Equation Ax=b	Oct 1
2	Oct 3 1.5 Solution Sets of Linear Systems	Oct 4 Discussion	Oct 5 1.7 Linear Independence	Oct 6 First Day Survey due	Oct 7 1.8 Introduction to Linear Transformations MATLAB HW 1 due Deadline to Add a Course	Oct 8
3	Oct 10 1.9 The Matrix of a Linear Transformation MyLab HW 1, 2 due	Oct 11 Discussion	Oct 12 2.1 Matrix Operations	Oct 13	Oct 14 2.2 The Inverse of a Matrix 2.3 Characterizations of Invertible Matrices	Oct 15
4	Oct 17 4.1 Vector Spaces and Subspaces MyLab HW 3 due	Oct 18 Discussion	Oct 19 Catch-up/Review	Oct 20	Oct 21 4.2 Null Spaces, Column Spaces, and Linear Transformations Midterm Exam 1 7:00pm-8:50pm Deadline to Drop without "W"	Oct 22
5	Oct 24 4.3 Linearly Independent Sets; Bases MyLab HW 4 due MATLAB HW 2 due	Oct 25 Discussion	Oct 26 4.5 The Dimension of a Vector Space	Oct 27	Oct 28 4.4 Coordinate Systems	Oct 29
6	Oct 31 3.1 Introduction to Determinants 3.2 Properties of Determinants MyLab HW 5 due	Nov 1 Discussion	Nov 2 3.2 Properties of Determinants 3.3 Cramer's Rule, Volume, and Linear Transformations	Nov 3	Nov 4 5.1 Eigenvectors and Eigenvalues MATLAB HW 3 due Deadline to Drop with "W"	Nov 5
7	Nov 7 5.2 The Characteristic Equation MyLab HW 6 due	Nov 8 Discussion	Nov 9 Catch-up/Review	Nov 10 Midterm Exam 2 8:00pm-9:50pm	Nov 11 Veterans Day Holiday - no class	Nov 12
8	Nov 14 5.3 Diagonalization MyLab HW 7 due	Nov 15 Discussion	Nov 16 6.1 Inner Product, Length, Orthogonality 6.7 Inner Product Spaces	Nov 17	Nov 18 6.2 Orthogonal Sets MATLAB HW 4 due	Nov 19
9	Nov 21 6.3 Orthogonal Projections MyLab HW 8 due	Nov 22 Discussion	Nov 23 6.4 The Gram-Schmidt Process	Nov 24 Thanksgiving Holiday - no class	Nov 25 Thanksgiving Holiday - no class	Nov 26
10	Nov 28 7.1 Diagonalization of Symmetric Matrices	Nov 29 Discussion	Nov 30 Catch-up/Review MyLab HW 9 due MATLAB Quiz opens at 12am	Dec 1 MATLAB Quiz closes at 11:59pm	Dec 2 Review MATLAB HW 5 due	Dec 3 Final Exam 7:00pm-9:59pm

Reading: Reading the sections of the textbook corresponding to each lecture is critical. Homework and exams will rely on material in the textbook; you are responsible for material in the assigned reading whether or not it is discussed in the lecture.

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Syllabus

Course: Math 18

Title: Linear Algebra

Credit Hours: 4 (Students may not receive credit for both Math 18 and 31AH.)

Prerequisite: Math Placement Exam qualifying score, or AP Calculus AB score of 3 (or equivalent AB subscore on BC exam), or SAT II Math Level 2 score of 650 or higher, or Math 4C, or Math 10A, or Math 20A, or consent of instructor.

Catalog Description: Matrix algebra, Gaussian elimination, determinants, linear and affine subspaces, bases of Euclidean spaces. Eigenvalues and eigenvectors, quadratic forms, orthogonal matrices, diagonalization of symmetric matrices. Applications. Computing symbolic and graphical solutions using MATLAB. See the UC San Diego Course Catalog.

Textbook: Linear Algebra and its Applications (6th Edition), by David C. Lay, Steven R. Lay, and Judi J. McDonald; published by Pearson (Addison Wesley).

Subject Material: We will cover parts of Chapters 1-7 of the text.

Lecture: Attending the lecture in-person or viewing the lecture podcast, is a fundamental part of the course; you are responsible for material presented in the lecture whether or not it is discussed in the textbook. You should expect questions on the exams that will test your understanding of concepts discussed in the lecture.

Discussion Sections: Discussion sections will be highly interactive. You will work in small groups on concept check and challenging exercises, to cement your understanding of core ideas from the course, and build a community of learning in this large class. Attendance of discussion sections is required, which means you must attend the section you are officially enrolled in. To gain full participation credit for the course, you must attend at least 8 out of the 10 discussion sections during the quarter. Full participation is required in order to earn credit for attendance. This includes contributing to group work and group discussions and staying engaged with the discussion material at all times. For remote discussions, this also includes having mics and cameras on at all times.

Homework: Homework is a very important part of the course and in order to fully master the topics it is essential that you work carefully on every assignment and try your best to complete every problem. Weekly homework is assigned through MyLab, accessible in Canvas. Unless otherwise stated, you have unlimited attempts on each homework problem: after three incorrect attempts, you will be offered a "Similar question" which is the same problem but with different numbers. All problems completed before the due date will receive full credit. You may continue to work on problems you did not complete before the deadline, for 50% credit until the last day of instruction. Your total homework score will be based on all the total possible homework points available; no homework assignment scores will be dropped at the end of the quarter.

MATLAB: In applications of linear algebra, the theoretical concepts that you will learn in lecture are used together with computers to solve large scale problems. Thus, in addition to your written homework, you will be required to do homework using the computer language MATLAB. The Math 18 MATLAB Assignments page contains all information relevant to the MATLAB component of Math 18. No late MATLAB assignments will be accepted. However, the lowest MATLAB assignment score will be dropped. There will be no make-up MATLAB quiz.

Exams: The midterm exams and final exam are scheduled for the Friday of Week 4, the Thursday of Week 7, and the first Saturday of exam week; see above for details. The midterms and the final exam are planned to take place in-person; this may change depending on UC San Diego policy and the public health situation at the time. More information will follow closer to these exams about precise logistics and policies.

Exam Versions: In cases of legitimate, well-documented, and unavoidable conflicts, there may be different versions of exams given, whether in-person or remote, synchronous or asynchronous. All versions of any exam will cover the same topics and will be calibrated to the same level of difficulty.

Collaboration Guidelines: You are allowed and even encouraged to collaborate with other students in the MyLab homework and MATLAB assignments. It is up to your own best judgment to make sure you are learning the material through those collaborations. No collaboration is allowed on the MATLAB quiz or exams. Moreover, "homework assistance" online sites such as Chegg are NEVER allowed for use in this class on homework, the MATLAB quiz, or exams. Any use of Chegg or similar services will be considered serious Academic Integrity violations.

Academic Integrity: In this course, and in your life as a UC San Diego student, we expect you to Excel with Integrity, and to adhere to the UC San Diego Integrity of Scholarship Policy.

Why? Math 18 is a core, foundational course for a wide variety of other mathematics, engineering, and physical science courses. This class is designed to aid your mastery of this important material, for its own sake and for the sake of your learning in all the further courses that rely heavily upon it. Every course component in Math 18 is formulated to cement your understanding, verify what you've mastered, and let us and you know where you need to prioritize your time and energy reviewing. All of our course policies around academic integrity are meant to make sure you are getting the best, most accurate information about your learning in this course. Any students who choose to violate our integrity policies are not just being unfair to their peers; they are ultimately cheating themselves out of a solid foundation in linear algebra.

That means we’re all in this together and we actually want the same thing. You, your peers, and the instructional team all want a class that has academic integrity. We want to be able to trust one another, and we want grades to be fair and honest reflections of learning. How can you ensure this type of environment is created in Math 18? Here are some specific examples:

Do not use, or post to "homework help" services such as Chegg. Do not post solutions to homework, the MATLAB quiz, or exam problems in any public forum (such as Piazza).
Do not collaborate on or copy the MATLAB quiz or exams. (There will be specific instructions about what that means in an Academic Integrity Pledge at the beginning of the MATLAB quiz or exam.)
Do not use any apps or sites that do the math for you, or connect you with people who will do the math for you. This will not aid in your learning.
Do not attempt to search for solutions to homework, the MATLAB quiz, or exam problems online or in sources outside of the course content. If you accidentally stumble upon a publicly available solution, you should notify your TA and instructor.

We are aware that the temptation to inappropriately collaborate, or use disallowed resources, is especially high right now during this period of remote/hybrid instruction. We urge you to remember that your integrity is worth more than any advantage you might hope to gain. We will (unfortunately) have to use all tools at our disposal to detect any academic integrity violations, for which there is a zero-tolerance policy. Penalties for these offenses always include assignment of a failing grade in the course, along with administrative sanctions, including up to suspension and dismissal from UC San Diego. Both failing grades and the administrative penalties could impact your ability to get into a capped major or be admitted into graduate or professional schools. Maintain your integrity, and don't risk major consequences to your career at UC San Diego and beyond.

Grading Policies: Final grades will be calculated as the maximum of the following two grading schemes:

2% Discussion Section participation based on on-time, full attendance and full participation of at least 8 discussion sections
5% MATLAB Assignments
5% MATLAB Quiz
20% MyLab Homework
19% Midterm Exam 1
19% Midterm Exam 2
30% Final Exam

2% Discussion Section participation based on on-time, full attendance and full participation of at least 8 discussion sections
5% MATLAB Assignments
5% MATLAB Quiz
20% MyLab Homework
28% Best Midterm Exam
40% Final Exam

Your letter grade will be determined by your cumulative average at the end of the term and will be based on the following scale:

A+	A	A-	B+	B	B-	C+	C	C-
97	93	90	87	83	80	77	73	70

The above scale is guaranteed: for example, if your cumulative average is 80, your final grade will be at least B-. However, we may adjust the above scale to be more generous.

Missed exam policy: There will be no make-up midterm exams; however, by design, the lowest midterm exam grade will be dropped. Nevertheless: you should make every effort to take the exams; this policy is meant only to accommodate true emergencies.

There will be no make-up final exam. If you miss the final exam, you will be assigned a score of 0 on that component of the class. If you have a conflict with the scheduled final exam time, you should not enroll in Math 18 this quarter. If an unexpected emergency or crisis prevents you from attending the final exam at the end of the quarter, and if you are in passing standing in the class at that time, you may be eligible for an Incomplete grade that will allow you to take the final exam at a later date. The circumstances under which Incompletes can be granted are tightly controlled by the university.

Here are two links regarding UC San Diego policies on exams:

Exam Responsibilities An outline of the responsibilities of faculty and students with regard to final exams
Policies on Examinations The Academic Senate policy regarding final examinations (These are the rules!)

Regrade Policy: Your MyLab homework and the MATLAB quiz will be autograded; your exams and MATLAB homework will be graded using Gradescope. If you find errors in the grading of your written work, you will have an opportunity to request a regrade through Gradescope. A regrade window will open three days after the scores are posted, and it will stay open for three days. During this time window you will be able to leave careful, thoughtful comments about where you feel a grading error was made. No regrade requests will be considered after the specified window closes. Please note: any regrade request may result in regrading of the entire assignment, and your overall score could go up or down.

Administrative Deadline: Your scores for all graded work will be posted in Gradescope and in Canvas. It is your responsibility to check your scores and contact your TA before the end of Week 10 to resolve recording errors. Questions regarding missing or incorrectly recorded scores will not be considered after the last day of instruction.

Considerate Conduct: Here are a few of our expectations for etiquette in and out of class.

Entering/exiting class: Please arrive on time and stay for the entire class/section period. If, despite your best efforts, you arrive late, please enter quietly through the rear door and take a seat near where you entered. Similarly, in the rare event that you must leave early (e.g. for a medical appointment), please sit close to the rear exit and leave as unobtrusively as possible.
Noise and common courtesy: When class/section begins, please stop your conversations. Wait until class/section is over before putting your materials away in your backpack, standing up, or talking to friends. Do not disturb others by engaging in disruptive behavior. Disruption interferes with the learning environment and impairs the ability of others to focus, participate, and engage.
Electronic devices: Please do not use devices (such as phones, laptops, and tablets) for non-class-related matters while in class/section. No visual or audio recording is allowed in class/section without prior permission of the instructor/TA.
Messaging etiquette: You are expected to write as you would in any professional correspondence. Email, Piazza, and other written communication should be courteous and respectful in manner and tone. Please do not send/post messages that are curt or demanding.

Equity, Diversity, and Inclusion: We are committed to fostering a learning environment for this course that supports a diversity of thoughts, perspectives, and experiences, and respects your identities, including race, ethnicity, heritage, gender, sex, class, sexuality, religion, ability, age, educational background, etc. Our goal is to create a diverse, inclusive, and empowering learning environment where all students feel comfortable and can thrive.

Our instructional staff will make a concerted effort to be welcoming and inclusive to the wide diversity of students in this course. If there is a way we can make you feel more included please let one of the course staff know, either in person, via email/discussion board, or even in a note under the door. Our learning about diverse perspectives and identities is an ongoing process, and we welcome your perspectives and input.

We also expect that you, as a student in this course, will honor and respect your classmates, abiding by the UC San Diego Principles of Community. Please understand that others’ backgrounds, perspectives and experiences may be different than your own, and help us to build an environment where everyone is respected and feels comfortable.

If you experience any sort of harassment or discrimination, please contact the instructor as soon as possible. If you prefer to speak with someone outside of the course, please contact the Office of Prevention of Harassment and Discrimination.

Students with Disabilities: We aim to create an environment in which all students can succeed in this course. If you have a disability, please contact the Office for Students with Disability (OSD), which is located in University Center 202 behind Center Hall, to discuss appropriate accommodations right away. We will work to provide you with the accommodations you need, but you must first provide a current Authorization for Accommodation (AFA) letter issued by the OSD. You are required to present your AFA letters to faculty (please make arrangements to contact your instructor privately) and to the OSD Liaison in the Math Department (Holly Proudfoot, hproudfood@ucsd.edu) in advance so that accommodations may be arranged. You will find more information here.

Basic Needs and Food Insecurities: If you are experiencing any basic needs insecurities (food, housing, financial resources), there are resources available on campus to help, including The Hub and the Triton Food Pantry. Please visit here to for more information.

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