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AMATH 352 A: Applied Linear Algebra And Numerical Analysis

Meeting Time: 
MWF 12:30pm - 1:20pm
CDH 109
Kelsey Maass
Kelsey Maass

Syllabus Description:

Lectures: MWF 12:30-1:20pm, CDH 109

Instructor: Kelsey Maass

  • Email:
  • Office Hours:
    • Wednesdays, 2:00-3:00pm, Lewis 129
    • Fridays, 10:00-11:00am, Lewis 129

Teaching Assistant: Micah Henson

  • Email:
  • Office Hours:

    • Mondays and Tuesdays, 3:30-4:20pm, CMU BO27 (Arts & Sciences Instructional Computing Lab)

Lecture Schedule: The planned schedule of lectures and reading list is available here.

Course Description: This course covers basic concepts of linear algebra with an emphasis on computational techniques. Linear algebra plays a fundamental role in a wide range of applications, including physical and social sciences, statistics, engineering, finance, and machine learning. 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. 

Prerequisites: MATH 126 or MATH 136

Course Materials: There is no textbook for this class. Instead, we will follow reference notes written by Randy LeVeque and Ulrich Hetmaniuk (available under the 'Files' tab).

The following texts are available online and can be used to supplement the course notes:

Some additional reference texts are:

  • Gilbert Strang, Introduction to Linear Algebra.
  • Peter J. Olver and Chehrzad Shakiban, Applied Linear Algebra
  • Richard L. Burden, and J. Douglas Faires, and Annette M. Burden, Numerical Analysis.

Computing: We will use Matlab for computation, so you must obtain access to either Matlab or Octave (a free alternative).

  • You may purchase a student copy of MATLAB here. (The $50 unbundled version will be sufficient for this class, but the $100 version has other useful packages.)
  • Alternatively, you may obtain a $35 Matlab license through the UW here. Note that these licenses will expire 6/30/2019.
  • Matlab is also available at several labs on campus, including the ICL (CMU B027). Remote access is available through the Mechanical Engineering department.
  • You may also download Octave, an open-source Matlab-like program. We will, however, not be available to provide support for this.

Homework: There will be a total of 8 graded homework assignments worth 40 points each (Homework 0 will not be graded). Each assignment will consist of a programming portion (submitted via Scorelator), and a written portion (submitted as a PDF through Canvas). Late homework will not be accepted, but you may drop your lowest homework score if and only if all homework assignments have been submitted with a good faith effort. 

  • Discussion Board: We will be using Piazza for class discussion. Rather than emailing questions to the teaching staff, I encourage you to post your questions to the discussion board. Participation, both asking and answering questions, is highly encouraged. 
  • LaTeX: We prefer that assignments are typeset and recommend using LaTeX. Typesetting Homework 1 is worth 5 bonus points, and there will be 2 bonus points for each typeset homework thereafter. If you don't want to download LaTeX, Overleaf is an online LaTeX editor. A quick tutorial to get started with LaTeX can be found here
  • Collaboration and Academic Honesty: You are encouraged to discuss and work in groups to solve problem sets - this may be a huge help in mastering the material. Whether you work in a group or by yourself, you must write up your own solutions and your own code. Copying or submitting work that is identical to a classmate's work or online solution is academic misconduct and will be reported according to the policies communicated by Community Standards & Student Conduct.

Exams: There will be two exams worth 100 points each. The midterm will be in class on Monday, February 11th, and the final exam will be in class on Friday, March 15th. 

Grading: Your course grade will be a weighted sum of your score on the homework (60%), midterm (20%), and final exam (20%). 

Access and Accommodations: It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law. If you have a temporary health condition or permanent disability that requires accommodation, you are welcome to contact Disability Resources for Students (DRS). If you have established accommodations with DRS, please communicate your approved accommodations with me at your earliest convenience so we can discuss your needs in this course. 

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: 
January 2, 2019 - 11:38am