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• Week 1: Introduction to Matrices. Vectors and system of linear equations. 
• Week 2: Solving system of linear equations using Gaussian Elimination Method, Gauss Jordan Method. 
• Week3: Inversion method in matrices, methods to calculate inverse of the given matrix. 
• Week 4: Introduction to Determinents.  Determinents by Cofactor Expansions Evaluation Determinents by row reduction. 
• Week 5: Properties and Applications of Determinents. Area and Volume of triangle and parallelogram. 
• Week 6: Introduction to Vector Space and Subspace. Norm, distance, Dot product, Cross product. 
• Week 7: Vector in 2-dimensional, 3-dimensional and n-dimensional space. Row space, Column space and Null space. 
• Week 8: Linear Combination, Linearly Dependent and Independent vectors. Basis and dimensions of a vector space. 
• Week 9: Mid Term Exam
• Week 10: Eigen values and Eigen vectors, Diagonalization. 
• Week 11: Rank, nullity and the fundamental matrix spaces. 
• Week 12: Orthogonal Bases and Gram Schmidt Ortho normalization Process.
• Week 13: Complex vectors and matrices, Complex numbers. Unitary and Hermitian matrices.
• Week 14: Markov Matrices, Linear Algebra for functions. 
• Week 15: Symmetric Matrices, Positive Definite Matrices, Singular Value Decomposition. 
• Week 16: Inner product spaces. 
• Week 17: Applications of Matrices in Engineering, Graphs, Networks. 
• Week 18: Final Term Exam.