[Free] Divide And Conquer: Computing Algorithm Design Strategy
Divide and Conquer, Introduction Control Abstraction, Binary search algorithm, quicksort algorithm, merge sort algorithm
What you’ll learn
- Students will learn what is divide and conquer strategy
- Students will learn which problems can be solved using divide and conquer strategy
- Students will learn how to solve given problem using divide and conquer strategy
Requirements
- Discrete Structures
- Data Structures and Algorithms
Description
Algorithm is a finite set of instructions which when followed accomplishes a particular task. There are various algorithm design strategies such as Divide and Conquer, Greedy method, Dynamic programming, Backtracking, Branch and Bound. For solving any problem we have to choose appropriate algorithm design strategy. Depending on problem type algorithm design strategy is selected.
This course explains divide and conquer algorithm design strategy in detail .A divide-and-conquer algorithm recursively breaks down a problem into two or more sub-problems of the same or related type, until these become simple enough to be solved directly. The solutions to the sub-problems are then combined to give a solution to the original problem.
In this course, we will study It’s Introduction, control abstraction and how to solve examples such as Binary search, quicksort and merge sort using divide and conquer strategy. Divide and conquer Computing Algorithm Design Strategy is divided into 4 sessions. In first session we will study introduction, control abstraction and recurrence equation of divide and conquer strategy. In second session, we will learn how to solve binary search algorithm using divide and conquer strategy. In third session we will learn how to solve Quick Sort Algorithm using divide and conquer strategy. In fourth session, we will learn how Merge Sort Algorithm works using divide and conquer strategy.
So this is the compact course on divide and conquer algorithm design strategy
Author(s): Rutuja Jadhav
