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### What is Design and Analysis Of Algorithms?

Design and Analysis of Algorithm is the branch of computer science and information technology introduced for designing algorithms to solve various types of problems in computing.

Algorithm is a set of instructions that specifies a process of operation to be carried out in order to solve a specific problem, task or class of problems.

An Algorithm is the best way to show the solutions to a particular problem in a very simple and efficient way. If we have an Algorithm for a particular problem, then we can easily implement it in any programming language, which means that the algorithm is independent of any programming languages.

As the speed and power of processors increases, performance is said to be less central when compared to other software quality characteristics like: security, extensibility, reusability, etc. Performance a very important factor in computing among other characteristics, this is because, the longer the computation time, the higher the cost of computation. Therefore, the study of Algorithms gives us the opportunity to optimize computing performance in general.

Design And Analysis of Algorithms are very important for designing an Algorithm in order to bring solutions to different types of problems in computer science and information technology. The major aspects of Algorithm design involves creating an efficient and detailed Algorithm to solve a particular problem in an efficient way with very minimum time and space.

To find solutions to a particular problem, different methods can be employed. Some of them can be efficient with regards to time usage, while other approaches can be memory efficient. However, one needs to keep in mind that time consumption and memory usage cannot be efficiently optimized at the same time. If we need an Algorithm to operate in lesser time we have to sacrifice more memory and if we require an algorithm to operate with lesser memory we need to have more time.

### Features Of Design and Analysis Of Algorithms:

The main features and characteristics of Algorithms are as follows:

1. Uniqueness: Algorithms must have a unique name.
2. Input/Output: Algorithms should have a clearly defined set of inputs and outputs.
3. Ordered Operations: Algorithms are usually well ordered and have specific and well-cut operations.
4. Definite Time: Algorithms all stop in a known amount of time. it doesn't run infinitely i.e, an algorithm must stop at some point.
5. Effective: Algorithms should be effective: The designed algorithm should solve the problem it was designed to solve. It should also be possible to demonstrate that the algorithm is feasible with just a paper and pencil.
6. Solution: The main aim of algorithm is to provide desired solution to a problem. An Algorithm must be able to provide the exact solution you are looking for.

### Benefits Of Design and Analysis Of Algorithms:

There are many benefits and advantages that we get from Designing and Analyzing Algorithms to solve a particular problem, some of them are:

1. It is a step by step representation of a solution given to a problem, which is the reason why an Algorithm is easy to understand.
2. An Algorithm makes use of a specific procedure. It doesn't depend on any programming language, so it is easy for anyone, even people without programming knowledge to understand.
3. Every step in an Algorithm has its own logical patterns it is very easy to debug.
4. By using an Algorithm, the problem is broken down, into little pieces or steps, from there it is easier for any programmer to convert it into an actual program.
5. It helps to provide solutions to complex problems in computing.

In The Full Course, you will learn everything you need to know about Design and Analysis of Algorithm with Certification to showcase your knowledge and competence.

### Design and Analysis Of Algorithms Course Outline:

Design & Analysis of Algorithms - Introduction

Design & Analysis of Algorithms - Analysis of Algorithms

Design & Analysis of Algorithms - Methodology of Analysis

Design & Analysis of Algorithms - Asymptotic Notations & Apriori Analysis

Design & Analysis of Algorithms - Space Complexities

Design & Analysis of Algorithms - Divide & Conquer

Design & Analysis of Algorithms - Max-Min Problem

Design & Analysis of Algorithms - Merge Sort

Design & Analysis of Algorithms - Binary Search

Design & Analysis of Algorithms - Strassen's Matrix Multiplication

Design & Analysis of Algorithms - Greedy Method

Design & Analysis of Algorithms - Fractional Knapsack

Design & Analysis of Algorithms - Job Sequencing with Deadline

Design & Analysis of Algorithms - Optimal Merge Pattern

Design & Analysis of Algorithms - Dynamic Programming

Design & Analysis of Algorithms - 0-1 Knapsack

Design & Analysis of Algorithms - Longest Common Subsequence

Design & Analysis of Algorithms - Spanning Tree

Design & Analysis of Algorithms - Shortest Paths

Design & Analysis of Algorithms - Multistage Graph

Design & Analysis of Algorithms - Travelling Salesman Problem

Design & Analysis of Algorithms - Optimal Cost Binary Search Trees

Design & Analysis of Algorithms - Binary Heap

Design & Analysis of Algorithms - Insert Method

Design & Analysis of Algorithms - Heapify Method

Design & Analysis of Algorithms - Extract Method

Design & Analysis of Algorithms - Bubble Sort

Design & Analysis of Algorithms - Insertion Sort

Design & Analysis of Algorithms - Selection Sort

Design & Analysis of Algorithms - Quick Sort

Design & Analysis of Algorithms - Radix Sort

Design & Analysis of Algorithms - Deterministic vs. Nondeterministic Computations

Design & Analysis of Algorithms - Max Cliques

Design & Analysis of Algorithms - Vertex Cover

Design & Analysis of Algorithms - P and NP Class

Design & Analysis of Algorithms - Cook’s Theorem

Design & Analysis of Algorithms - NP Hard & NP-Complete Classes

Design & Analysis of Algorithms - Hill Climbing Algorithm

Design & Analysis of Algorithms - Exams and Certification 