Design and Analysis of Algorithms(DAA)
Description
The objective of the course is to teach techniques for effective problem solving in computing. The use of different paradigms of problem solving will be used to illustrate clever and efficient ways to solve a given problem. In each case emphasis will be placed on rigorously proving correctness of the algorithm. In addition, the analysis of the algorithm will be used to show the efficiency of the algorithm over the naive techniques.
What Will I Learn?
- Ability to analyze the performance of algorithms.
- Ability to choose appropriate algorithm design techniques for solving problems.
- Ability to understand how the choice of data structures and the algorithm design
- methods impact the performance of programs.
- To clear up troubles the usage of set of rules design methods including the
- grasping approach, divide and overcome, dynamic programming, backtracking and
- department and certain.
- To understand the variations among tractable and intractable problems.
- To introduce p and np classes.
Topics for this course
98 Lessons60h
Introduction
What is Algorithm and Characteristic18:25
Difference Between Algorithm, Pseudocode and Program10:40
Analyzing Algorithms10:40
Rules for calculating time complexity13:23
Time Complexity Examples7:10
Space Complexity analysis7:10
Growth of Function in Algorithm: Asymptotic Notations7:10
Introduction to Recurrence Relation11:31
Recurrences Substitution Method11:31
Recurrences Substitution Method examples11:31
Recursion Tree Method for Solving Recurrences7:22
Recursion Tree Method for Solving Recurrences Example6:11
Master Method for Solving Recurrence Relation15:20
Master theorem Solved Examples22:14
Sorting Algorithm
Advanced Data Structures
Divide and Conquer
Greedy Methods
Dynamic Programming
Backtracking
Branch and Bound
Selected Topics
Notes
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