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AMATH 352 A: Applied Linear Algebra and Numerical Analysis

Summer Term: 
Meeting Time: 
MWF 10:50am - 11:50am
DEN 258
Kelsey Marcinko
Kelsey Marcinko

Syllabus Description:

AMATH 352: Applied Linear Algebra and Numerical Analysis

Welcome to another step in expanding your mathematical knowledge! This course covers basic concepts of linear algebra with an emphasis on computational techniques. Nearly every discipline with a quantitative component including engineering, physical sciences, social sciences, finance, computer graphics, big data, and machine learning rely on linear algebra. Many hard problems in these fields can be reduced to or approximated by linear algebra problems. In this course, we will study vectors and matrices, linear systems, least squares problems, and eigenvalue problems. Matrix decompositions (e.g., LU, QR, SVD) play an important role in the course.

General Information

Instructor: Kelsey Marcinko,

TA: Yu-Chen Cheng, 

Note: Please use the Piazza page for course content and homework related questions which may benefit classmates. Email may be used for communication that addresses individual concerns.

Class: MWF in DEN 258, 10:50-11:50am

Instructor office hours:

  • Wednesday 9-10am, Gerberding B054, conference room.
  • Thursday 1-2:30pm, ICL (Instructional Computing Lab), Communications Building, B027.

TA office hours: Wednesday 1-3pm, Gerberding B054, conference room

Applied Math Department: Lewis Hall is under construction. For Applied Math staff, please see Gerberding B054.



For this course, you are required to have access to a copy of Applied Linear Algebra by Olver and Shakiban. The current book is published by Springer, though a copy of the older Pearson text will also be acceptable. Please make sure to obtain a digital or physical copy of the textbook for the first week of the course.


Learning Objectives

This course is meant to be an extension of your previous mathematical coursework. Thus, one of the goals is for you to incorporate concepts from previous courses with new material. Recall that MATH 126 (and consequently MATH 124 and 125) or MATH 136 are prerequisites for this course.


This course will combine linear algebra theory and application, as well as numerical analysis. Students in this course have a wide range of backgrounds and will likely be challenged by different aspects of the course. I expect that you will be stretched by this course, but I am confident that you can succeed through persistence and consistent engagement with the material. I will provide a variety of ways to engage with the content, but you are ultimately responsible for developing your own knowledge in this field.


By the end of this course, you should be able to...

  • Interpret and use terminology and notation presented in assigned reading and in class.
  • Define key terms in your own words.
  • Perform calculations to determine properties of matrices, sets of vectors, and systems of linear equations
  • Identify and perform necessary calculations to solve a given problem.
  • Explain and analyze the relationships between key terms, theoretical concepts, algorithms, and decompositions. This may occur in the context of a particular problem or for a general case.
  • Evaluate numerical solutions or methods in terms of accuracy, stability, and/or computational efficiency.
  • Explain and summarize the implications of properties of a given system of linear equations or a matrix.
  • Using words and pseudocode, write out the steps for solving a problem computationally.
  • Write Matlab code to implement algorithms and solve problems.



  • Homework assignments, solutions, assigned reading, and gradebook can be found at the Canvas course webpage:
  • We will use Piazza for the course discussion board. You are encouraged to ask questions and respond to classmates' questions! The discussion board is located here: If you have used Piazza before, you should now have access to the discussion page for this course. If you are new to Piazza, please check your UW email for account activation.
  • Coding portions of the homework will be submitted to Scorelator. See Canvas for resources for working with Scorelator.
  • PollEverywhere: We will sometimes use PollEverywhere to encourage participation and discussion. Please bring a cell phone or computer to class for this purpose. Your device should not be used in class for other purposes (e.g. social media, internet, etc.) Using a phone or computer for purposes unrelated to this course may result in a reduction of your participation grade.


Assigned Reading

Learning goal: By the end of this course, you should be able to read a section in a math textbook and be able to identify the key points as well as begin to understand the presented concepts. Textbook sections often include some information that may seem superfluous. In this course, you will practice sorting through the information that is presented to find the main idea and what concepts will be useful. These skills will benefit you in your future academic and career pursuits.


To facilitate this, you will complete assigned reading weekly. You will be given a combination of guiding reading questions and prompts to generate your own questions. Reading responses will be submitted through Canvas and will guide and inform the class discussion of the material.



Matlab will be used heavily in this course so you will need access to it. There are several ways to get access.

  • Previously-purchased temporary licenses through the UW web store will expire on July 1st.
  • Beginning this year, students may now obtain free of charge Matlab license for use on computers they own personally. All licenses expire at the end of the licensing year, June 30th. To register your UW student Mathworks account and download the software go to the UW portal at Mathworks:
  • You can alternately purchase a student edition through the UW bookstore or the Mathworks website. There is a basic version for $49 and a version with the most popular toolboxes for $99. This version of Matlab will be functional for multiple years.
  • There is Matlab access in some computer labs on campus, including the Instructional Computing Lab.


Class Participation

Attendance is required in this course. Each class period will begin with active engagement in questions generated by student response to required reading. Lectures will consist of active student engagement in the material, clarification and expansion on reading material, working through example problems led by the instructor or in small groups. Participation will be demonstrated through in-class activities (including PollEverywhere). You are also encouraged to demonstrate participation through use of the course discussion board on Piazza.


In-class Activities

Days on which we will be doing in-class activities will be announced ahead of time in the course announcements.You may be required to complete some reading or watch a video before class to prepare. The in-class activities will be completed in groups of two or three students and will be graded. The lowest score will be dropped. Some activities will require Matlab so at least one member of your group needs to have access to Matlab in class.



Homework will be given on a weekly basis. Each homework assignment will likely have two parts: a written part and a Matlab part. Each part will be submitted separately (more on that below) and  both parts will be due at the beginning of class on the due date. You are required to read the provided "Homework Guidelines" on the Canvas webpage. Homework assignments will also be posted on Canvas.

  • Collaboration: Collaboration and study groups are encouraged! Every student must submit their own assignment consisting of their own work, which should never be identical to the work of a classmate. Copying a classmate's work or online solution is academic misconduct and will be reported according to the policies communicated by Community Standards & Student Conduct (CSSC). Any form of dishonesty in an assignment will lead to a zero on the assignment. Other consequences, including a failing grade in the course, will be determined based on the seriousness of the offense or multiple offenses at the instructor's discretion. Your continued enrollment in this course constitutes acceptance of the course and university policies.
  • Late assignments: No late assignments will be accepted for any reason. In the rare event of an emergency, with sufficient documentation, a homework will be dropped and other homeworks re-weighted.
  • Scoring: I expect neat, complete, correct solutions to the assigned problems. Selected problems from each handwritten homework assignment will be graded for a total of 20 possible points. One or two randomly selected problems will be graded for a total of 16 points. 4 points will be awarded for completion. Partial credit will be given for work shown, but no credit will be given for answers with no work. Your final answer for each problem must be clearly marked. You may drop the lowest homework score only if all homework assignments are submitted.
  • Homework Submission

    • The written portion of the homework will be submitted on paper at the beginning of class on the due date. The written portion of the assignments will be graded for completeness and several problems will be randomly chosen and graded for correctness. Graded work will be returned in class.
    • The Matlab portion of the homework will be submitted and graded online using a system called Scorelator. A link to Scorelator and instructions can be found in Canvas.
    • You have up to 3 attempts in Scorelator per homework to get everything correct. Your score for each homework will be the best grade out of all 3 attempts. (In particular, if you get a perfect score on the first attempt, you do not need to submit again.) These extra attempts are intended to help with submission issues; they are not a good way to debug your code. You should be confident that your code is correct (and it should certainly run on your own machine) before you submit to scorelator.
    • An anti-cheating system is used to compare your code with that of other students in this class (including previous quarters). You should not copy code from anyone else.
    • You should access Scorelator using Firefox or Internet Explorer (not Safari or Chrome). If you use a different browser to submit your assignment, your submission may be corrupted, resulting in a lower grade for that attempt.
    • Do not use the Scorelator email address for questions about this class. (It is out of date and no one will see it.) Instead, ask your question in class, on the discussion board, or in office hours. If you think there is a problem with Scorelator, you can email me.
    • The default login name is (UW NetID) (Your UW email address.)



  • Reading response and class participation: 15%. Reading questions, class participation, and in-class activities will compose 15% of your course grade. Participation may also be demonstrated through posting questions and responses to the online discussion board.
  • Homework: 25%. Assignments will be submitted approximately weekly.
  • Exams: 30% each x 2. Tentatively scheduled for July 24th and August 23rd. In-class. The second exam will focus on the material from the latter half of the course. However, topics build on each other, so familiarity with previously covered material is necessary.


Academic Responsibility

Students shall abide by the University of Washington Academic Responsibility policies, which are outlined at Violations will be reported to the appropriate Dean's Representative and through the webpage for Community Standards and Student Conduct. The instructor reserves the right to assign a failing grade for the course for serious violations of student conduct.

Note: Use of websites or online forums which provide solutions for class assignments is not allowed. You are also not allowed to distribute course materials to any individual or corporation outside of this course, AMATH 352 Su19.


Access and Accommodations

Your experience in this class is important to me. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to me at your earliest convenience so we can discuss your needs in this course.


If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), you are welcome to contact DRS at 206-543-8924 or or DRS offers resources and coordinates reasonable accommodations for students with disabilities and/or temporary health conditions. Reasonable accommodations are established through an interactive process between you, your instructor(s) and DRS. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law.

Catalog Description: 
Analysis and application of numerical methods and algorithms to problems in the applied sciences and engineering. Applied linear algebra, including eigenvalue problems. Emphasis on use of conceptual methods in engineering, mathematics, and science. Extensive use of MATLAB package for programming and solution techniques. Prerequisite: MATH 126 or MATH 136. Offered: AWSpS.
GE Requirements: 
Natural World (NW)
Last updated: 
August 2, 2019 - 9:00pm