MTH 341: Introduction to Linear Algebra
Section A
Fall 2025
Department of Mathematics
University of Portland
Fall 2025
Department of Mathematics
University of Portland
Syllabus
About the Class
Description
This course provides an introduction to the core principles of linear algebra, including systems of linear equations, matrix operations, vector spaces, and linear transformations. Emphasis is placed on both analytical and computational techniques for solving linear systems, as well as geometric intuition and visualization. Applications to physical systems are explored to highlight the relevance of linear algebra across disciplines.
Instructor Information
- Instructor: Dr. Alex John Quijano
- Office: Buckley Center 279
Lectures and Discussions
This course meets on Mondays, Wednesdays, and Fridays. Homework will be scheduled for alternating Mondays. The typical class routine will include pre-reading assignments before each class, followed by a short lecture or demonstration, worksheet activities, group presentations, and discussions.
The course schedule and location is:
- Section A: MWF 12:30 PM - 1:25 PM, Franz Hall 205
Textbook
This course uses the following textbook –which is free to access– for reading and practice.
- Hefferon J (2022). Linear Algebra, 4th edition. OpenIntro., https://hefferon.net/linearalgebra/.
Credit Hours and Prerequisites
- Credit hours: 3
- Prerequisites: MTH 202 (Calculus II) with a grade of C- or higher.
Communication Tools
Class Website
The syllabus, tentative topics schedule, and other information are posted on the course website.
You can access the course website at mth-341a-fa25.
Note that this website can also be viewed in Teams.
Microsoft Teams
We will be using Teams as the main real-time communication tool for general announcements, question-answering discussions, and direct messages. I added you to the Teams page already, so you just need to log in using your UP credentials. If not, then send a request when you log in. Let me know if you need any assistance.
I recommend that you install the Teams software on your own machine for easy and stable access, instead of accessing Teams on the browser.
The Teams for this course is MTH-341A-fa25.
Note that this course website and textbook can be accessed in Teams.
My UP email is quijano@up.edu.
If you prefer communicating through email, note that I have set up an email filter for this course, and you must put the “MTH 341” keyword in your subject line.
It is easy for me to get notice of your email if you put the keyword in the subject line. Concise and specific messages are helpful, so I know how I can best help you.
Assignment Tools
Moodle
We will be using the course Moodle page for submitting assignments and giving feedback.
The Moodle for this course is MTH-341A - fa25 - Introduction to Linear Algebra. You are already listed in Moodle for this course using your UP account.
Posit Cloud
We will be using the Python programming language as a computational tool for some assignments. This tool is free and open-source. We will use the Posit Cloud service.
Posit Cloud is an online computing environment that supports computations in Python.
Python is a powerful language for mathematical computing, widely used for symbolic algebra, numerical analysis, data visualization, and building custom models.
Jupyter is an interactive computing environment that lets you combine live code, math, visualizations, and narrative text for exploring, documenting, and sharing mathematical analyses and simulations.
Create a free account at Posit Cloud Sign-Up using your UP email. Note that you must use your UP email for me to add you into the course’s workspace in Posit Cloud. You will receive an email inviting you into the workspace at the first week of the semester.
If you’d like to set up Python on your own computer, start by installing Python, then install Jupyter to run and share code interactively. Feel free to reach out if you’d like help with any step!
Python instructions and materials will be provided ad hoc.
Amendment 1: The subsection “Wolfram” was removed.
Learning Goals
Learning Outcomes
Upon completion of the course, you will be able to:
- Understand the basic structures of linear systems.
- Understand the solution types of linear systems.
- Solve linear systems using a variety of analytical methods.
- Evaluate and visualize the properties of vectors and matrices.
- Evaluate and visualize linear transformations and projections.
- Use numerical methods to solve linear systems.
- Apply linear algebra to solve physical systems.
- Write clear and concise mathematical solutions to linear algebra problems.
- Communicate effectively about linear systems with other students, instructors, and professionals.
- Work independently and as part of a team to solve linear algebra problems.
- Effectively use technology to support the analysis and solution of linear systems.
Learning Objectives
The following learning objectives are designed to build on one another, with some overlap. The goal is to help you achieve proficiency in these areas.
Topic Category | Learning Objectives |
---|---|
Linear Systems | Compute the solution set for a system of linear equations (or vector or matrix equation) in order to characterize the system. |
Translate between a system of linear equations, a vector equation, a matrix equation, and an augmented matrix. | |
Explain why a matrix isn’t in reduced row echelon form (RREF) and use the row reduction algorithm to put a matrix in RREF. | |
Express the solution set for a linear system in parametric vector form and interpret this geometrically, distinguishing between homogeneous and nonhomogeneous systems. | |
Matrix Algebra | Perform basic algebraic operations on vectors and matrices using standard notation. |
Determine when a square matrix is invertible, compute its inverse, and use the inverse to solve linear systems. | |
Linear Transformations | Translate between a linear transformation of Euclidean spaces and its standard matrix and perform related computations. |
Determine whether or not a map between vector spaces is linear. | |
Represent a composition of linear transformations in terms of appropriate matrix operations. | |
Determine when transformations are one-to-one or onto. | |
Find a basis for the kernel and image of a linear transformation and verify the rank-nullity theorem holds for a given map | |
Vector Spaces | Characterize sets of vectors as linearly independent or dependent, using definitions, vector equations, and calculations as justification. |
Characterize spans, using definitions, vector equations, and calculations as justification. | |
Verify that a given set with vector addition and scalar multiplication specified satisfies the axioms for a vector space or explain why a such a set fails to be a vector space. | |
Determine whether a given subset of a vector space is a subspace. | |
Explain why a set of vectors is or is not a basis for a vector space or subspace and use this to determine dimension. | |
Eigentheory | Identify the eigenvalues and eigenvectors for a given matrix or transformation. |
Find a basis for the eigenspace associated to a given eigenvalue of a matrix. | |
Diagonalize a matrix or explain why it is impossible to do so using eigentheory. | |
Model Physical Systems | Use linear systems to represent physical mechanics. |
Solve a linear system to balance a chemical equation and solve RLC circuits. | |
Use linear algebra to solve linear least-squares regression. | |
Use linear algebra for network analysis. | |
Use Technology | Understand the basics of using Python for Linear Algebra. |
Use Python to analyze, visualize, and solve linear systems. |
Topics Schedule
Week | Day | Topic |
---|---|---|
1 | M 8/25 | Orientation and Linear Systems |
W 8/27 | Gauss’s Method | |
F 8/29 | Solution Sets | |
2 | M 9/1 | Echelon Form |
W 9/3 | Row Reduction | |
F 9/5 | Linear Combination | |
3 | M 9/8 | Vectors |
W 9/10 | Subspace and Span | |
F 9/12 | Linear Independence | |
4 | M 9/15 | Basis |
W 9/17 | Dimension | |
F 9/19 | Vector Space | |
5 | M 9/22 | Isomorphisms |
W 9/24 | Review | |
Tu 9/23 to F 9/26 | Exam 1 | |
6 | M 9/29 | Characteristics |
W 10/1 | Homomorphisms | |
F 10/3 | Null Space and Column Space | |
7 | M 10/6 | Linear Maps |
W 10/8 | Matrices | |
F 10/10 | Matrix Sums and Scalar Products | |
8 | M 10/13 | Fall Vacation |
W 10/15 | Fall Vacation | |
F 10/17 | Fall Vacation | |
9 | M 10/20 | Matrix Multiplication |
W 10/22 | Matrix Inverse | |
F 10/24 | Change of Basis | |
10 | M 10/27 | Projection |
W 10/29 | Review | |
Tu 10/28 to F 10/31 | Exam 2 | |
11 | M 11/3 | Determinants |
W 11/5 | Properties of Determinants | |
F 11/7 | Similarity | |
12 | M 11/10 | Diagonalizability |
W 11/12 | Eigentheory | |
F 11/14 | Eigenvalues and Eigenvectors | |
13 | M 11/17 | Eigendecomposition |
W 11/19 | Row Space and Left Null Space | |
F 11/21 | Four Fundamental Subspaces of Linear Algebra | |
14 | M 11/24 | Review |
M 11/24 to W 11/26 | Exam 3 | |
F 11/28 | Thanksgiving Vacation | |
15 | M 12/1 | Proper Orthogonal Decomposition |
W 12/3 | Singular Value Decomposition | |
F 12/5 | Review | |
16 | M 12/8 - Th 12/11 | Final Exam |
Academic Support
Help Hours
Dr. Alex John Quijano
- Walk-in Monday to Friday at 1:30 PM - 2:30 PM, Buckley Center 279
- One-to-One, Buckley Center 279 or in Teams
Click on the link to sign-up for a 15-minute session.
My walk-in help hours start week 2. Note that you can bring a fellow student with you when you sign-up for a session. Just click the “Add Guests” link when you sign-up, and add in your fellow student’s UP email. If you need more than 15 minutes, you can book at least two consecutive sessions.
The Learning Commons\(^*\)
Students may receive academic assistance through Learning Commons tutoring services and workshops. The Co-Pilot peer tutoring program provides students with opportunities to work with other students to get help in writing, math, group projects, and many other courses. Schedule an appointment to meet with a Co-Pilot (tutor) by visiting the Learning Commons website (www.up.edu/learningcommons). Students can also meet with a Co-Pilot during drop-in hours. Check the Learning Commons website or stop by the Learning Commons in BC 163 to learn more about their services. Co-Pilots are a wonderful support along your academic journey.
Math Resource Center
Appointment-based tutoring accepts appointments starting week 1 and sessions start week 2. Visit the Math Resource Center website to sign-up for an appointment. Drop-in tutoring is Monday to Thursday, 3:00 PM - 7:00 PM in BC 163 and starts week 2. Check the Math Resource Center website or drop by the center for more information.
Help Hours Guidelines
It is strongly recommended that you attend the walk-in help hours or set up a one-to-one meeting with the me if you feel like you are falling behind during our in-person class activities, or if you just need to clarify concepts discussed in class. In order to be more productive during a one-to-one meeting (or the walk-in help hours), these are three recommendations before you come in:
- List all gaps in knowledge you have (missed concepts) or list all concepts that were unclear to you during class. We will address them one by one.
- Prepare questions you want answered and be ready to show relevant materials.
- Regarding assignments, prepare to show (a) what are the steps you have tried and (b) what are the errors you encountered and the strategies you have tried.
Note that these are recommendations so that you can get the most out of the help hours allocated for you. If you just want to come in and chat about something else, feel free to do so. If the dedicated time for one-to-one meeting does not work for you, send me a message to set up an appointment.
Collaboration Policy
I expect you to participate in the class through lectures, class activities, discussions, homework, and other engagements. I also expect you to make use of opportunities to get help outside of class (help hours, Teams, email, tutoring) if you need help. Concise and specific messages are the most helpful so I know how I can best help you.
You are encouraged to participate in discussions with your peers regarding assignments. However, each student must take responsibility and ownership of their work and submit their work individually, except for group projects.
Assessment
Assessment Disclosure Statement\(^*\)
Student work products for this course may be used by the University for educational quality assurance purposes. For reasons of confidentiality, such examples will not include student names.
Standards-Based Grading
Learning ODEs demands focus, rigorous examination of the concepts you have encountered, and a process of ongoing refinement and improvement. You will be assessed on your proficiency in solving a variety of ODEs, both graphically and analytically, using different methods. You will have opportunities to demonstrate your proficiency, revise your work, and reflect on your growth in identifying the type of ODE, determining appropriate solution methods, and analyzing the behavior of the solutions.
This course uses a standards-based grading system, which emphasizes mastery of specific learning objectives. This approach is more precise and motivating than traditional grading methods and fosters a more equitable learning environment. Key features of standards-based grading include:
- A clear focus on mastering defined learning objectives
- The use of diverse assessment methods to evaluate understanding
- Regular, detailed feedback to guide your progress
- Support in setting meaningful goals and tracking your growth
This system prioritizes learning and personal development, enabling you to excel and reach your highest potential.
General Marking Guide
Each assignment will be graded according to the general marking guide detailed below. You will be given feedback on your assignment and learning process to improve your performance. Note that each assignment has its own rubric guided by these general guidelines and the assignment’s learning objectives.
Given the following marks, your work:
Mark | Rubric Description |
---|---|
Outstanding (O) |
Demonstrates a full understanding of the material, clearly and concisely explains concepts, applies them correctly and efficiently to solve problems, and may extend the concepts to new situations. |
Excellent (E) |
Demonstrates an approximate understanding of the material, may have made minor errors but is able to correct them and explain the reasoning, solves problems correctly, and may need more time or practice to improve efficiency. |
Acceptable (A) |
Demonstrates some understanding of the material but makes errors, can solve some problems, may need help with more difficult ones, and may need to work on improving problem-solving skills and reasoning. |
Needs Improvement (NI) |
Shows potential but needs more work, may have made several errors, is unable to solve problems, and needs to focus on understanding the material and developing problem-solving skills. |
Needs Major Improvement (NMI) |
Shows little understanding of the material, may have made many significant errors, is unable to solve problems, and needs to focus on building a foundational understanding of the material. |
Missing (M) |
Shows incomplete (either entirely or partially) or incomprehensible work. |
Note that these are categorical marks (not numerical scores).
Final Course Grades
Assignment | Rank | Mark | A | B | C | D |
---|---|---|---|---|---|---|
Exams | 1 | O | 90% | - | - | - |
E | - | 80% | - | - | ||
A | - | - | 70% | - | ||
NI | - | - | - | 60% | ||
Homeworks | 2 | O | 100% | - | - | - |
E | - | 90% | - | - | ||
A | - | - | 80% | - | ||
NI | - | - | - | 70% | ||
Worksheets | 3 | Completed | 90% | 80% | 70% | 60% |
The above table shows the percent of given assignments. These percentages are minimum requirements for each letter grade. The rank determines the importance of each assignment where 1 means the highest rank and 3 means lowest rank.
If you need more assistance on understanding your overall standing in this course, I encourage you to communicate with me directly.
Assignments
Submission Guidelines
You need to submit all assignments online through Moodle. Your assignments must be in a single
.py
or.ipynb
) if any.
Your work must be labeled correctly and clearly written. Homework,
worksheets, and exams can be electronically hand-written or typed but
must be uploaded to Moodle as a single .pdf
file. Here are
additional submission rules:
- If you choose to handwrite your answers on paper, scan your document using a scanner app to ensure the text is clear. I recommend using the “Adobe Scan” app, which is available for both Android and iOS.
- If the assignment involves a Python coding component, you must
include all relevant Python code files (
.py
and.ipynb
) that generated all outputs, plots, and analysis. Your Python code must be properly documented or with comments.
Worksheets
There will be worksheets every class day except for exam weeks. The purpose of the worksheets is for in-class group work and activities.
You must submit your worksheet individually by end-of-class or end-of-day. Your name must exist in your worksheet and the names of your collaborators.
Worksheets are marked mostly on completion, and partially on correctness. It will be marked either pass or fail, there will no detailed feedback on worksheets, and no opportunities for revisions and make-up.
Homeworks
Homework is assigned every Monday. The purpose of the homework is to provide practice with problems, and it will include tasks that involve Python.
You must submit your homework individually by the end of the day on Friday of the week it is assigned.
Homeworks are marked using the general grading guide and will be returned with detailed feedback.
Homework Revisions
You can revise your homework for an up-grade, meaning - for example - a grade of “NI” can be up-graded to “A”.
Here are the qualifications and requirements for homework revisions:
- A homework mark of “NMI”, “NI”, “A”, or “E”.
- The revised homework must be completed, meaning all parts should have your full written solutions.
- Homework marked with “M” is disqualified for revisions, but you can still use them as practice.
Here are the rules for homework revisions:
- Homework revisions are accepted within one week of the homework being returned to you, otherwise the grade is set.
- You have one chance to revise your homework.
Amendment 2: The rule “You can revised your homework multiple times as long as it is not marked as”M”.” was changed to “You have one chance to revise your homework.”
Exams
Exams are given in two parts which are in written and oral forms. Below are the description of each part of the exams.
Written
The written part of the exam allows you demonstrate your understanding of the material in written form. This part will be evaluated on the details of your computations and solutions.
Written exams will be graded on 3 components:
Written Component | Description |
---|---|
Methodology | The method should be sound and well-founded. It should be based on a solid understanding of the underlying principles. The method should be applied correctly and consistently. |
Reasoning | The solution method should be explained in a clear and logical way. The steps of the method should be justified and explained. The reasonableness of the solution should be justified. |
Writing | The solution process should be written in a clear and concise way. The steps of the method should be easy to follow. The graphs/diagrams/equations should be clear and helpful. The mathematical notation should be used clearly and correctly. |
Here are the rules for the written part of the exams:
- Written exams are take-home exam and given Monday of an exam week.
- Written exams are due on the day of your scheduled oral part of the exam.
- Late submissions are not accepted unless the instructor allows.
Oral
The oral part of the exam allows you to demonstrate your understanding of the material verbally. It is administered mostly in dialog style during exam days. The oral exam lasts only ten to fifteen minutes and includes predetermined questions about problems from the written exam, which are provided to the student ahead of time. This part will be evaluated on your ability to explain key concepts and navigate through different ways to solve problems, rather than detailed solutions.
Oral exams will be graded on 3 components:
Oral Component | Description |
---|---|
Knowledge | This includes the student’s ability to recall and apply mathematical concepts and procedures. The student should be able to answer questions about the material in a clear and concise way, and they should be able to solve problems using a variety of methods. |
Communication | This includes the student’s ability to explain their thinking clearly, concisely, and timely. The student should be able to use mathematical language fluently, and they should be able to communicate their ideas in a way that is understandable. |
Problem-solving | This includes the student’s ability to identify and solve mathematical problems. The student should be able to think critically about problems, and they should be able to develop and implement strategies for solving them. |
Here are the rules for the oral part of the exams:
- You must sign-up for a time slot on an exam week 24 hours in advance.
- You must submit your written exam at the beginning of the oral exam.
- You may have all other resources with you during the oral exam, that includes books and online resources.
- You may not communicate with others during the exam except to me.
- You may not ask conceptual questions to me except for clarifying questions about the problem, and minor computations.
The grade you will receive for exams are a breakdown of your written and oral exam results with detailed feedback.
Here is how you can sign-up for the exam (oral part):
- Introduction to Linear Algebra Exam
Click on the link to sign-up for a 15-minute session.
Exam Retakes
Your exams can be revised and you can retake both written and oral parts. Exam retakes allows you to have your exams up-graded, meaning - for example - a grade of “NI” can be up-graded to “A”.
Exam retake procedure are similar to the original exam. The written part is your revised exam and the oral part is explaining your revisions and responding to feedback from the last oral exam.
Here are the qualifications for exam retakes:
- An exam grade of “NMI”, NI”, “A”, or “E”.
- The revised exam must be completed, meaning all parts should have your full written solutions. Incomplete work is disqualified for revisions and retakes.
Here are the rules for exam retakes:
- Exam retakes must be done within one week of the exam being returned to you, otherwise the grade is set.
- If you need to retake an exam more than one week of the exam being returned to you, let me know for a discussion.
- The same written and oral exam part rules apply for exam retakes.
- You have one chance to retake an exam.
Amendment 3: The rule “You have one chance to retake an exam.” was added.
Here is how you can sign-up for the exam (oral part) retakes:
- Introduction to Linear Algebra Exam Retakes
Click on the link to sign-up for a 15-minute session.
Make-up Exams
You can make-up exams due to extenuating circumstances. Please let me know if you can’t make it to an exam day. If you missed an exam day, please let me know as soon as possible to discuss the next steps.
Here are the rules of make-up exams:
- A missed exam day means that you will automatically receive a grade of M for that particular exam.
- You need to have a prior discussion with me before you can schedule a make-up exam.
- Make-up exams by appointment must be scheduled 24 hours in advance.
- Make-up exams must be done within one week of the original exam day.
- If you need to make-up an exam more than one week of the original exam day, let me know for a discussion.
Here is how you can sign-up for the exam (oral part) make-ups:
- Introduction to Linear Algebra Exam Make-Ups
Click on the link to sign-up for a 15-minute session.
Final Exam
The final exam includes the written and oral parts. This exam will be cumulative. Makeup exams are not allowed during finals week. The same written and oral exam part rules apply for the final exam, except that retakes are no longer allowed.
The final exam days are:
- Monday 12/8 to Thursday 12/11
Academic Integrity
The Honor Code Statement
I commit to upholding the code of academic integrity by demonstrating ethical and responsible academic practices and adhering to the principles of academic integrity.
You are encouraged to utilize all resources available to you, including course materials, online references, and collaborative discussions with your classmates. However, you must adhere to the following principles:
- Follow the Academic Integrity Policy: Ensure all work is your own or properly credited where collaboration or external resources are involved.
- Comply with the Course AI Policy: Any use of AI tools must align with the course-specific AI guidelines provided. Misuse of AI will be considered a violation of academic integrity.
- Adhere to Referencing and Citation Guidelines: Properly cite all external sources used in your work to give appropriate credit and avoid plagiarism.
- Uphold the Academic Honor Code: I trust you to maintain the highest standards of honesty and integrity in your work.
- Take Ownership of Your Work: You must contribute meaningfully and be prepared to explain and defend your work.
Code of Academic Integrity\(^*\)
The University of Portland is a diverse academic community of learners and scholars who are dedicated to freely sharing ideas and engaging in respectful discussion of those ideas to discover truth. Such pursuits require each person, whether student or faculty, to present truthfully our own ideas and give credit to others for the ideas that they generate. Thus, cheating on exams, copying another student’s assignment, including homework, or using the work of others without proper citation are some examples of violating academic integrity.
Especially for written and oral assignments, students have an ethical responsibility to properly cite the authors of any books, articles, or other sources that they use. Students should expect to submit assignments to Turnitin, a database that ensures assignments are original work of the student submitting. Each discipline has guidelines for how to give appropriate credit, and instructors will communicate the specific guidelines for their discipline. The Clark Library also maintains a webpage that provides citation guidelines at https://libguides.up.edu/cite.
The misuse of AI to shortcut course learning outcomes will be treated as a violation of academic integrity comparable to plagiarism or cheating. Faculty are responsible for including a written “Course AI Policy” in their syllabi that clearly states what they consider appropriate and inappropriate uses of AI in the context of their courses. Students are responsible for using AI in ways that do not detract from the established learning outcomes of the course. All members of the scholarly community are responsible for demonstrating sound judgment in discerning when and how to utilize AI in their work, upholding standards of citation, originality, and integrity.
Course AI Policy
The use of generative AI —such as Copilot, Gemini, or ChatGPT— is encouraged and allowed in all of its capacity. However, students must use these tools ethically and responsibly. To use generative AI responsibly in this class, students should grasp underlying concepts, acknowledge AI’s assistance, protect data privacy, verify information, and uphold academic honor code. AI should be seen as a learning aid, not a replacement for critical thinking.
Ethics of Information\(^*\)
The University of Portland is a community dedicated to the investigation and discovery of processes for thinking ethically and encouraging the development of ethical reasoning in the formation of the whole person. Using information ethically, as an element in open and honest scholarly endeavors, involves moral reasoning to determine the right way to access, create, distribute, and employ information, including: considerations of intellectual property rights, fair use, information bias, censorship, and privacy. More information can be found in the Clark Library’s guide to the Ethical Use of Information at libguides.up.edu/ethicaluse.
Other Expectations
Deadline Extensions
If you need more time to submit an assignment, you may request an extension by following these steps:
- Communicate with me at least 12 hours before the deadline.
- Specify the exact day you plan to submit your work or the number of extra days you need.
- Please ensure that you adhere to the established timeline for submitting assignments, as it is important to maintain fairness and avoid over-reliance on extensions.
Submitting a few hours late is usually not a major issue, as long as I receive your work before I begin marking and providing feedback. An extension is not required in such cases. Extensions for in-class assignments –such as worksheets or activities– will only be granted if I decide to extend the deadline for the entire class.
Late Assignments
You are expected to turn in all completed assignments on time. Circumstances that may disallow you to turn in your work on time –such as a medical reason– are understandable. Please let me know if you have missed the deadline way beyond its original posted date without prior communication regarding extensions. Because every assignment is an important aspect of your learning in this class, we will discuss when you will turn in the assignment as well as decide upon an acceptable consequence for your turning it in late. I am committed to successfully helping you learn from this course.
Withdrawal Procedures
It is the student’s responsibility to drop the course if he or she is no longer planning on attending the course or filling the other course requirements. In order to drop, the student must use and Add/Drop form available at the Registration Office. If a student does not properly withdraw from a course, he or she may receive an F for the course. A properly withdrawn student will receive a W. The last day to withdraw is Monday, November 24th.
Appointment Cancellations
Please try to show-up to your scheduled appointments. You can cancel your appointments, but it is strongly recommended that you cancel 24 hours before your scheduled time so that other students can schedule when a spot opens. You can reschedule for a different day and time if you need to. If you have extenuating circumstances, please let me know as soon as possible to discuss next steps.
Attendance and Participation
Attendance is not tracked. However, participation is highly recommended and often tracked through assignments and general behavior. You are expected to actively participate in this class. Participation includes coming to class on time, being prepared, being willing to ask questions and share ideas, setting up study groups outside of class, attending tutoring and help hour sessions, posting helpful resources online, and contributing to the discussion channels. Group and individual presentation of ideas is a suggested component of participation.
Absences
Generally, students are expected to attend all class sessions according to the instructor’s direction. Students who feel unwell should not attend class in person. These students should inform their instructor as soon as possible. Should the instructor need to miss class, the course may be temporarily conducted remotely. Should the instructor be unable to teach for an extended period of time, the respective department or unit will find a substitute to continue the course.
Incompletes
An incomplete “I” will only be considered when the quality of a student’s work is satisfactory (C- or better), but for some essential reason the course has not been completed by the student. An “I” is reserved for emergency situations only. To request an incomplete, the student must submit a typed, signed and dated letter stating the reason(s) why an incomplete is appropriate. The letter should also contain the conditions for the completion of work. Acceptance of the request shall be at the discretion of the instructor, Department Chair, and/or Dean of the College of Arts & Sciences.
Accessibility Statement\(^*\)
The University of Portland strives to make its courses and services fully accessible to all students. Students are encouraged to discuss with their instructors what might be most helpful in enabling them to meet the learning goals of the course. Students who experience a disability are encouraged to use the services of the Office for Accessible Education Services (AES), located in the Shepard Academic Resource Center (503-943-8985). If you have an AES Accommodation Plan, you should meet with your instructor to discuss how to implement your plan in this class. Requests for alternate location for exams and/or extended exam time should, where possible, be made two weeks in advance of an exam, and must be made at least one week in advance of an exam. Also, if applicable, you should meet with your instructor to discuss emergency medical information or how best to ensure your safe evacuation from the building in case of fire or other emergency. All information that students provide regarding disability or accommodation is confidential. All students are responsible for completing the required coursework and are held to the same evaluation standards specified in the course syllabus.
Mental Health Statement\(^*\)
Anyone can experience problems with their mental health that interfere with academic experiences and negatively impact daily life. If you or someone you know experiences mental health challenges at UP, please contact the University of Portland Counseling Center (https://www.up.edu/counseling/) in the upper level of Orrico Hall (down the hill from Franz Hall and near Mehling Hall) at 503-943-7134 or hcc@up.edu. Their services are free and confidential. In addition, mental health consultation and support is available through the Pilot Helpline by calling 503-943-7134 and pressing 3. All UP students also have access to teletherapy through BetterMynd. The University of Portland Campus Safety Department (503-943-4444) also has personnel trained to respond sensitively to mental health emergencies at all hours. Remember that getting help is a smart and courageous thing to do – for yourself, for those you care about, and for those who care about you. For more information on health and wellness resources at UP go to www.linktr.ee/wellnessUP.
Non-Violence Statement\(^*\)
The University of Portland is committed to fostering a safe and respectful community free from all forms of violence. Violence of any kind, and in particular acts of power-based personal violence, are inconsistent with our mission. Together, all UP community members must take a stand against violence. Learn more about what interpersonal violence looks like, campus and community resources, UP’s prevention strategy, and what we as individuals can do to assist on the Green Dot website, www.up.edu/greendot. Further information and reporting options may be found on the Title IX website, www.up.edu/titleix.
Materials
You are required to read the materials, and are strongly encouraged to actively participate in class discussions and complete the assignments efficiently to deepen your understanding and succeed in the course.
Class Readings
The “Read” column in the table below contains page numbers (Pg.) or chapters (ch.) on which it refers to a label in the Books & Online Resources List. For example “Ch. One I.1 [1]” refers to Chapter One section I.1 of the textbook titled Linear Algebra.
Topic | Read |
---|---|
Orientation and Linear Systems | Ch. One I [1] |
Gauss’s Method | Ch. One I.1 [1] |
Solution Sets | Ch. One I.2-I.3 [1] |
Echelon Form | Ch. One III [1] |
Row Reduction | Ch. One III.1 [1] |
Linear Combination | Ch. One III.2 [1] |
Vectors | Ch. One II.1-11.2 & Ch. Two I-I.1 [1] |
Subspace and Span | Ch. Two I.2 [1] |
Linear Independence | Ch. Two II-II.1 [1] |
Basis | Ch. Two III-III.1 [1] |
Dimension | Ch. Two III.2 [1] |
Vector Space | Ch. Two III.3 [1] |
Isomorphisms | Ch. Three I-I.1 [1] |
Characteristics | Ch. Three I.2 [1] |
Homomorphisms | Ch. Three II-II.1 [1] |
Null Space and Column Space | Ch. Three II.2 [1] |
Linear Maps | Ch. Three III-III.1 [1] |
Matrices | Ch. Three III.2 [1] |
Matrix Sums and Scalar Products | Ch. Three IV-IV.1 [1] |
Matrix Multiplication | Ch. Three IV.2-IV.3 [1] |
Matrix Inverse | Ch. Three IV.4 [1] |
Change of Basis | Ch. Three V-V.2 [1] |
Projection | Ch. Three VI-IV-3 [1] |
Determinants | Ch. Four I & I.2 [1] |
Properties of Determinants | Ch. Four I.3 & Ch. Four II-II.1 [1] |
Similarity | Ch. Five II-II.1 [1] |
Diagonalizability | Ch. Five II.2 [1] |
Eigentheory | Ch. Five II.3 [1] |
Eigenvalues and Eigenvectors | - |
Eigendecomposition | - |
Row Space and Left Null Space | - |
Four Fundamental Subspaces of Linear Algebra | - |
Proper Orthogonal Decomposition | - |
Singular Value Decomposition | - |