Instructor

Debasattam Pal

Semester

Spring ‘20

Course Difficulty

The course is fairly intuitive and should be easy for someone who is interested in linear algebra.

Time Commitment Required

Watching lectures and solving homeworks should be enough to get a decent grade. On average , 2 hours per week outside lecture time should be enough.

Grading Policy and Statistics

Refer ASC

Attendance Policy

No policy enforced. Strongly encouraged to attend the classes though.

Pre-requisites

Linear Algebra

Evaluation Scheme

Homeworks - 20 , Quizzes - 20 , Midsem - 20 , Endsem - 40

Topics Covered in the Course

Gaussian Elimination , LU decomposition , Sensitivity of Linear Systems , Least Squares Problem , QR decomposition , Gram Schmidt Process , Singular Value Decomposition , Eigenvalues and Eigenvectors , QR algorithm

Teaching Style

Live lectures. Spent a considerable portion of every class in clearing doubts from previous lecture.

Tutorials/Assignments/Projects

Homeworks contain questions from the textbook itself

When to take this course?

4th semester. 4th or 6th semester

References Used

Fundamentals of Matrix Computations by David Watkins

Review By: Arush Krishnasya Tadikonda