A computer program is a collection of instructions to perform a specific task. For this, a computer program may need to store data, retrieve data, and perform computations on the data.

A data structure is a named location that can be used to store and organize data and an algorithm is a collection of steps required to solve a particular problem. Learning data structures and algorithms allow us to write efficient and optimized computer programs.

## What is an algorithm?

In computer programming terms, an algorithm is a set of well-defined instructions to solve a particular problem. It takes a set of input(s) and produces the desired output. For example,

An algorithm to multiply two numbers:

Take two number inputs

Multiply numbers using the * operator

Display the result

Qualities of a good algorithm :

Input and output should be defined precisely.

Each step in the algorithm should be unambiguous.

Algorithms should be the most effective among many different ways to solve a problem.

An algorithm shouldn't include computer code. Instead, the algorithm should be written in such a way that it can be used in different programming languages.

## What are data Structures?

Data structure is a storage that is used to store and organize data. It is a way of arranging data on a computer so that it can be accessed and updated efficiently.

### Types of Data Structure

Data structures are divided into two categories; Linear data structure and Non-linear data structure. Let's learn about each type in detail.

### Linear Data Structures

In linear data structures, the elements are arranged in sequence one after the other. These are easy to implement. However, when the complexity of the program increases, the linear data structures might not be the best choice because of operational complexities.

Some popular linear data structures are:

**Array Data Structure:** In an array, the same types of elements are stored in continuous memory.

**Stack Data Structure:** In the stack, elements are stored in the LIFO principle. That is, the last element stored in a stack will be removed first. It works just like a pile of plates where the last plate kept on the pile will be removed first.

**Queue Data Structure:** The queue follows FIFO principle i.e first in first out; where the first element stored in the queue will be removed first. It works just like a queue of people at the ticket counter where the first person in the queue will get the ticket first.

**Linked List Data Structure:** In linked list, data elements are connected through a series of nodes. And, each node contains the data items and addresses to the next node.

### Nonlinear data structures

Unlike linear data structures, elements in non-linear data structures are not in any sequence. Instead, they are arranged in a hierarchical manner where one element will be connected to one or more elements.

Non-linear data structures have two types; graph and tree-based data structures.

**Graph Data Structure:** In a graph, each node is called a vertex and each vertex is connected to other vertices through edges.

**Popular Graph-Based Data Structures:**

Spanning Tree and Minimum Spanning Tree

Strongly Connected Components

Adjacency Matrix

Adjacency List

**Trees Data Structure: S**imilar to a graph, a tree is also a collection of vertices and edges. However, in the tree data structure, there can only be one edge between two vertices.

**Popular Tree-based Data Structure**

Binary Tree

Binary Search Tree

AVL Tree

B-Tree

B+ Tree

Red-Black Tree

## Why Data Structures and algorithms?

Data structures and algorithms (DSA) are the essential building blocks of coding. Understanding data structures' importance can help you better grasp how your code operates and how your computer handles the enormous amount of incoming data. Knowing how algorithms work enables you to develop strategies that can help you optimize your code even further, reduce the amount of time and space required for code execution, and effectively use your mathematical skills.

## Placements and Job Opportunities

Many people have the desire to become engineers. Whatever their driving forces, all engineering students must go through the same hiring procedure to accomplish their objectives and land a job opportunity at their preferred firms.

A company's hiring procedure includes several coding tests, technical interviews, and HR interviews.

Do you realize what the initial few rounds of the interviews hinge on, even though your personality can handle the latter part of them? DSA, you guessed it right.

# Improved problem-solving abilities

It doesn't matter how many programming languages you know or courses you've taken for development disciplines like web, app, or desktop development to qualify as a coder or software engineer. Your ability to solve problems in real life is what you need first to comprehend.

There is a reason why all businesses require candidates to have a solid understanding of DSA. That is because problem-solving and developing more effective technology solutions both depend on data structures and algorithms.

Have you ever considered how social media websites manage massive amounts of data and interactions? Have you ever given any thought to how Google Maps is used? To determine the best and quickest path between a source and a destination, Google Maps employs a data structure known as "graphs" and several algorithms. Similarly, social media platforms like Facebook link their people through graphs.

Look up the real-world applications of the DSA you are learning, and you will be able to begin thinking appropriately. The next time you start a software project, having this information will help you select the ideal data structure and method.

# Switching roles

Learn the significance of DSA if you want to gain a better engineering career or if you are currently employed in a different field than engineering. The easiest method for professionals to learn a new skill is to enroll in boot camps that provide them with learning modules and real-world experience.