Linear Algebra

  • College Of Computing & Information Technology |

Description

This course illustrates the nature of mathematics as a blend of technique, theory, and applications. The important problem of solving systems of linear equations leads to the algebra of matrices, determinants, vector spaces, bases and dimension, linear transformations, and Eigen values. Vector spaces are studied in an abstract setting, examining the concepts of linear independence, span, bases, subspaces, and dimension. There follows a discussion of the association between linear transformations and matrices.

Program

Software Engineering bachelor`s degree Program

Objectives

  • • Learn important concepts of linear algebra.
    • Be familiar with the ideas of matrices and their applications in solving problems involving systems of linear equations.

Textbook

David C. Lay, Steven R. Lay, Judi J. McDonald, Linear Algebra and Its Applications, Pearson.

Course Content

content serial Description
1Matrices: Definition - Addition –Scalar multiplication – Matrices with special properties.
2Matrix multiplication – Matrix transpose – Determinants.
3Matrix inverse.
4Systems of linear equations: Linear equations - Reduced Row Echelon Form and Row Operations – Matrix Rank.
5Rank and systems of linear equations - The Homogeneous Case.
6Systems of linear equations the Non-Homogeneous Case – Criteria for Consistency and Uniqueness.
7Criteria for Consistency and Uniqueness.
8Vector Spaces: Vector Algebra [definition-addition-multiplication by scalar-dot product- cross product].
10Definitions of vector space and Basic Concepts – Subspaces part 2.
11Definitions of vector space and Basic Concepts – Subspaces part 3.
12Introduction to Linear Transformations.
13Linear Transformations: Mappings - General Properties of Linear Transformations.
14Eigenvalues and Eigen.
15Diagonalization.
9Definitions of vector space and Basic Concepts – Subspaces part 1.
1Matrices: Definition - Addition –Scalar multiplication – Matrices with special properties.
2Matrix multiplication – Matrix transpose – Determinants.
3Matrix inverse.
4Systems of linear equations: Linear equations - Reduced Row Echelon Form and Row Operations – Matrix Rank.
5Rank and systems of linear equations - The Homogeneous Case.
6Systems of linear equations the Non-Homogeneous Case – Criteria for Consistency and Uniqueness.
7Criteria for Consistency and Uniqueness.
8Vector Spaces: Vector Algebra [definition-addition-multiplication by scalar-dot product- cross product].
10Definitions of vector space and Basic Concepts – Subspaces part 2.
11Definitions of vector space and Basic Concepts – Subspaces part 3.
12Introduction to Linear Transformations.
13Linear Transformations: Mappings - General Properties of Linear Transformations.
14Eigenvalues and Eigen.
15Diagonalization.
9Definitions of vector space and Basic Concepts – Subspaces part 1.

Markets and Career

  • Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
  • Electrical power feeding for civil and military marine and aviation utilities.
  • Electrical works in construction engineering.

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