Course Details
Subject {L-T-P / C} : MA6655 : Mathematical Techniques for Data Analysis { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Manas Ranjan Tripathy
Syllabus
Module 1 : |
Vector spaces, Bases and dimensions, Linear transformations, Matrix algebra, Eigen values and Eigen vectors.
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Course Objective
1 . |
To learn Vector spaces, Bases and dimensions, Linear transformations, Matrix algebra, Eigen values, and Eigen vectors. |
2 . |
To study Lines and hyperplanes, convex sets, convex hull and their properties, Formulation of a Linear Programming Problem, Theorems dealing with vertices of feasible regions and optimality. |
3 . |
To study Graphical solutions, the Simplex method (including the Big M method and two-phase method), infeasible and unbounded LPPs, alternate optima, |
4 . |
To learn the Dual problem and duality theorem. Transportation problems, Assignment problems, Travelling salesman problems. |
Course Outcome
1 . |
1. The students will learn and understand the basics of Vector spaces, Bases and dimensions, linear transformations, Matrix algebra, eigenvalues, and eigenvectors.
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Essential Reading
1 . |
K. Hoffman and R. A. Kunze, Linear Algebra, Prentice Hall of India |
2 . |
H. A. Taha, Operations Research: An Introduction, Pearson Education Limited |
Supplementary Reading
1 . |
H. Dym, Linear algebra in Action, American Mathematical Society |
2 . |
W. L.Winston, Operation Research, Thomson Learning EMEA |