Textbook: Linear Algebra (fifth edition) by O. Bretscher.
Instructor: Monica Visan, 6167 Math Sciences Building.
Office Hours: Tuesday 10am-12pm or by appointment.
Midterm 1: will cover the material presented in the first 11 lectures; see the table below. You can find a practice midterm here.
Midterm 2: will cover all the material presented in the first 19 lectures; see the table below. You can find a practice midterm here.
Final: will cover all the material presented this quarter. You can find a practice final here.
Homework: There will be weekly homework. It is due in class on Fridays. It will be posted on this webpage the weekend before it is due. Further information is given below.
Grading: Homework: 10%; Midterm 1: 20%; Midterm 2: 20%; Final: 50%. No exceptions.
Student Math Center
Syllabus: The following table will be updated as we progress through the course.
|1||1.1-2||Linear systems, Gauss-Jordan elimination|
|2||1.3||Gauss-Jordan elimination, matrix algebra|
|4||2.2||Linear transformations in Geometry|
|5||2.3||Matrix algebra, products|
|6||2.3-4||Matrix algebra, inverses|
|7||2.4, 3.1-2||Matrix inverses, kernel and image of linear transformations, subspaces of Rn|
|8||3.1-2||Linear independence, bases|
|9||3.1-3||Linear independence, bases for the kernel and image of a linear transformation, dimension.|
|12||5.1-2||Orthogonality, orthonormal bases, Gram-Schmidt process|
|13||5.2||Gram-Schmidt process, QR-factorization|
|14||5.1 and 5.4||Orthogonal projection, least squares methods|
|15||5.1-4||Orthogonal transformations, orthogonal matrices|
|20||7.1-2||Eigenvalues and eigenvectors, computing eigenvalues|
|21-22||7.3||Computing eigenvectors, diagonalization of matrices|
|23-26||8.1-3||Symmetric matrices, quadratic forms, SVD (singular-value decomposition)|