Details of MA2102 (Autumn 2019)

Level: 2 Type: Theory Credits: 3.0

Course CodeCourse NameInstructor(s)
MA2102 Linear Algebra I Somnath Basu

Basic Material: System of linear equations, matrices, elementary row and column operations, echelon forms etc.

Vector Spaces: Definition of a vector space, subspace, quotient space and their examples; linear independence; basis and dimension; scalar product; orthogonal basis and the Gram-Schmidt orthogonalization process.

Matrix and Determinant: Trace of a matrix, rank of a matrix, rank-nullity theorem, properties of determinant, non-singularity, similar matrices, elementary matrices, partitioned matrices, special types of matrices, change of basis, Dual spaces.

Eigenvalues and Eigenvectors: Eigenvalues and eigenvectors of a matrix, characteristic polynomial, Diagonalization.

Similarity: Orthogonal, unitary and Hermitian matrices, similarity and unitary similarity, Schurs triangularization theorem and the spectral theorem for normal matrices (statements only)


  1. Axler, S., Linear Algebra Done Right, Springer-Verlag.

  2. Friedberg, S.H., Insel, A.J. and Spence, L.E., Linear Algebra, Prentice-Hall.

  3. Halmos P.R., Finite Dimensional Vector Spaces, Springer.

  4. Hoffman, K. and Kunze, R., Linear Algebra, Prentice-Hall.

  5. Horn, R. and Johnson, C.R., Matrix Analysis, Cambridge University Press.

  6. Kumeresan, S., Linear Algebra: Geometric Approach, Narosa Publishing

  7. Lang, S., Introduction to Linear Algebra, Springer-Verlag.

  8. Rao, A.R. and Bhimasankaran, P., Linear Algebra, Hindustan Book Agency.

Course Credit Options

Sl. No.ProgrammeSemester NoCourse Choice
1 IP 1 Not Allowed
2 IP 3 Not Allowed
3 IP 5 Not Allowed
4 MR 1 Not Allowed
5 MR 3 Not Allowed
6 MS 3 Core
7 RS 1 Not Allowed
8 RS 2 Not Allowed