Introduction to system of linear equations
Matrix form of system of Linear Equations
Consistent and inconsistent systems
Gauss-Jorden Method
Homogeneous system of equations
Gaussian Elimination method
Introduction to vector in plane
Vector in RPn
Vector form of straight line
Linear Combinations
Geometrical interpretation of solution of Homogeneous and Non-homogeneous equation
Traffic Flow Problem
Electric circuit Problem
Economic Model
Introduction to linear transformations
Matrix transformations
Domain and range of linear transformations
Geometric interpretation of linear transformations
Matrix of linear transformations
Definition of inverse of a matrix
Algorithm to find the inverse of matrices
LU factorization
Introduction to determinants
Geometric meaning of determinants
Properties of determinants
Crammer Rule
Cofactor method for finding the inverse of a matrix
Definition of vector spaces
Subspaces
Spanning set
Null Spaces and column spaces of linear transformation
Linearly Independent sets and basis
Bases for Null space and Kernal space
Dimension of a vector space
Introduction to Eigen value and Eigen vectors
Computing the Eigen values
Properties of Eigen values
Diagonalization
Applications of Eigen values
Lectures (audio/video aids), Written Assignments/ Quizzes, Tutorials, Case Studies relevant to engineering disciplines, Semester Project, Guest Speaker, Industrial/ Field Visits, Group discussion, Report Writing
Mid Term, Report writing/ Presentation, Assignments, Project Report, Quizzes, Final Term
There are 133 total credit hours to complete the Software Engineering degree.