Description

This course introduces the mathematical design and analysis of computer algorithms. Algorithm complexity, growth of functions, recurrences will be covered. Algorithm design techniques such as divide-and-conquer, dynamic programming and greediness will be introduced. Moreover, well known algorithms for e.g., sorting, searching, graph problems and computational geometry will be developed.

Program

Computer Science Program.

Objectives

1. Apply asymptotic time complexity analysis to choose among competing algorithms.
2. Construct and solve recurrence equations describing the asymptotic time complexity of a given algorithm.
3. Identify the best algorithm design technique for a given problem.
4. Implement efficient algorithms using the appropriate data structures.

Textbook

Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms, The MIT Press

Course Content

content serial	Description
1	Introduction
2	Algorithms analysis and sorting techniques
3	Recurrences
4	Brute Force Algorithm
5	Greedy Algorithms
6	Greedy Algorithms (cont.)
7	7th Week Exam
8	Dynamic programming
9	Divide and Conquer
10	Back-Tracking
11	Graph Algorithms
12	12th Week Exam
13	String Algorithms
14	Computational Geometry
15	Revision
16	Final Exam
1	Introduction
2	Algorithms analysis and sorting techniques
3	Recurrences
4	Brute Force Algorithm
5	Greedy Algorithms
6	Greedy Algorithms (cont.)
7	7th Week Exam
8	Dynamic programming
9	Divide and Conquer
10	Back-Tracking
11	Graph Algorithms
12	12th Week Exam
13	String Algorithms
14	Computational Geometry
15	Revision
16	Final Exam

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.

Degree Bachelor
Code: CS312
Credit hrs: 3
Prequisites: CS212

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Computing Algorithms