#### Specific Objectives of course:

Linear algebra is the study of vector spaces and linear transformations. The main objective of this course is to help students learn in  rigorous manner, the tools and methods essential for studying the solution spaces of problems in mathematics, engineering, the natural sciences, and social sciences and develop mathematical skills needed to apply these to the problems arising within their field of study; and to various real world problems.

#### System   of   Linear   Equations:

Representation  in   matrix   form. Matrices. Operations on matrices. Echelon and reduced echelon form. Inverse of a matrix (by elementary row operations). Solution of linear system. Gauss-Jordan method. Gaussian elimination.

#### Determinants:

Permutations of order two and three and definitions of determinants of the same order. Computing of determinants. Definition of higher order determinants. Properties. Expansion of determinants.

#### Vector   Spaces:

Definition   and   examples,   subspaces.   Linear combination  and  spanning  set.  Linearly  Independent sets.  Finitely generated vector spaces. Bases and dimension of a vector space. Operations on  subspaces, Intersections, sums and  direct sums  of subspaces. Quotient Spaces.

#### Linear mappings:

Definition and examples. Kernel and image of a linear mapping. Rank and nullity. Reflections, projections, and homotheties. Change of basis. Eigen-values and eigenvectors. Theorem of Hamilton-Cayley.

#### Inner   product   Spaces:

Definition   and   examples.   Properties, Projection. Cauchy inequality. Orthogonal and orthonormal basis. Gram Schmidt Process. Diagonalization.