Lectures: MWF 10:50-11:50 am, CMU 120
Instructor: Saumya Sinha
Office Hours - Tue 10:30am - Noon, LEW 129; Fri 1 - 2:30pm, LEW 129; or by appointment.
Teaching Assistant: Kelsey Maass
Lecture Schedule: The planned schedule of lectures and reading list is available here.
Prerequisites: MATH 126 or MATH 136.
Course description: Linear algebra plays a fundamental role in a wide range of applications from physical and social sciences, statistics, engineering, nance, computer graphics, big data and machine learning. This course covers basic concepts of linear algebra, with an emphasis on computational techniques. We will study vectors, vector spaces, linear transformations, solving linear systems, least squares problems, matrix decompositions (e.g. LU, QR, SVD), and eigenvalue problems. The emphasis will be on practical aspects of linear algebra and numerical methods for solving these problems.
Course Materials: There is no textbook for this class. Instead, we will follow reference notes written by R. LeVeque and Ulrich Hetmaniuk (available under the 'Files' tab).
The following texts are freely available online and can be used to supplement the course notes.
- Jim Hefferon, Linear Algebra. The LaTeX source files and answers to exercises are available from Jim Hefferon's web page.
- Cleve Moler, Numerical Computing with MATLAB. Cleve Moler is the original developer of MATLAB.
Additional reference texts are:
- G. Strang, Introduction to Linear Algebra, Wellesley Cambridge Press, 2009.
- R.L. Burden and J.D. Faires, Numerical Analysis.
Computing: We will use Matlab for computation, and you must obtain access to Matlab or Octave (a free alternative) for your use.
- You may purchase a student copy of Matlab here. (The unbundled version ($50) will be sufficient for this class, but the $100 version has other useful packages.)
- Alternatively, you may obtain a Matlab license through the University for $30 (UW Matlab). Note that these will only be available from July 1st.
- Matlab is also available at several labs on campus, including the ICL (Communications, B022). Remote Access is available through the Mechanical Engineering department.
- You may also download Octave, an open-source Matlab-like program, here. We will, however, not be available to provide support for this.
Homework: There will be a total of seven graded homeworks worth 40 points each, due every Monday at the beginning of class. (Homework 0 will not be graded.) A subset of the problems will be graded for credit while the rest for completeness. I strongly urge you to type up the homework using LaTeX or another typesetting software. Typesetting the first homework will be worth 5 bonus points, and typesetting subsequent homeworks will each be worth 2 bonus points. Typed homeworks may be submitted through Canvas, while handwritten ones must be submitted in person.
You may obtain LaTeX here. You may also use LyX which has a GUI for typesetting in LaTeX. Overleaf is an online LaTeX editor which I also find very useful. A quick tutorial to get started with LaTeX can be found here and here.
Each homework will also consist of a programming portion and you will be asked to submit your Matlab scripts online via Scorelator where they will be graded automatically. More details on Scorelator submissions to follow.
Late policy: You may submit at most one homework up to a week late without any penalty. Subsequent homeworks will not be accepted after the due date.
You are encouraged to discuss and collaborate with your peers on the homework, but solutions must be written up individually and not shared with others. Questions may be brought to class, office hours and the Canvas discussion board. Please note that homework-related questions will not be answered via email.
Exams: The midterm will be in class on Wednesday, July 19. The final exam will be in class on Friday, August 18.
Your course grade will be a weighted sum of your score in the homeworks, midterm and final, added in the proportions 50%, 20% and 30% respectively.