Fourth Semester

COURSE TITLE:            Linear Algebra (NS - 120)

Credit Hours:              3 (Theory)

Pre-requisites:            Calculus and Analytical Geometry

 

COURSE OBJECTIVES:

 

Introduce the matrix theory and the use of matrices in the solution of engineering problems.

 

 

COURSE DESCRIPTION:

 

Vectors, Vector Spaces, Matrices & Determinants, Cofactor and Inverse, Rank, Linear Independence, Solution of system of Linear systems, Positive Definite matrix, Linear Transformations, Operations on matrices, Inner products, orthgonality and least squares, Eigenvalue & Eigenvectors. Numerical linear algebra. Applications to Systems of Equations and to Geometry, Singular Value Decomposition.

 

Recommended Books:

 

§  Gilbert Strang, "Linear Algebra and Its Applications", 4th Edition, Thomson Brooks/ Cole, 2007.

§  James M Ortega, "Matrix Theory – A Second Course", Plenum, 1991.

§  Otto Bretscher, "Linear Algebra with Applications", 3rd Edition, Prentice Hall, 2005.

§  David Poole, "Linear Algebra – A Modern Introduction", Brooks/Cole, 2003

COURSE TITLE:            Data Structure and Algorithms (CS - 225)

Credit Hours:              3 (Theory) + 1 (Lab)

Pre-requisites:            Computer Programming

 

COURSE OBJECTIVES:

 

·         To understand. the design and analysis of fundamental data structures and algorithms

·         Discuss the use of primitive data types and built-in data structure.

·         Employ different types of data structures such as arrays, lists, stack, queues, trees, and graphs.

·         Analyze sorting, searching, recursion, divide-conquer, hashing techniques.

·         Write programs that use each of the following data structures: arrays, strings, linked lists, stacks, queues, and hash tables

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COURSE DESCRIPTION:

 

Introduction to data structures; Basic algorithms analysis; Big O, little o, omega and theta notation, Representation of numeric data, Pointers and references, Data structure operations, Searching and sorting techniques, Recursion, Fundamental data structures - implementation strategies for stacks, queues and linked lists; Implementation strategies for tree and graph algorithms; Traversal techniques Hash tables, files, Applications of data structures (e.g. data compression and memory management).

 

Lab portion:       Programming problems based on object oriented concepts relevant to the theory portion

Tool Used:          C++ or Java

 

Recommended Books:

 

§  Data Structures and Algorithm Analysis in C++, 4th Edition, Mark Weiss, Prentice Hall, 2014

§  Data Structures and Algorithm Analysis in Java, 3rd Edition, Mark Weiss, Prentice Hall, 2014