Breadth First Search Tutorial | Graph in Data Structure Part 2 | BFS in Java | Shortest Path @SCALER

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What is a Graph?
In data structures, a graph is a collection of nodes (vertices) connected by edges. These connections can represent relationships between various entities or data points. Graphs are used to model complex networks, such as social media connections, transportation routes, and more, providing a versatile way to visualize and analyze interconnected data.

What is DSA?
DSA stands for Data Structures and Algorithms. It refers to a set of techniques and methods used to organise and manipulate data in a computer program. Data structures are a way of organising and storing data in a way that enables efficient access and modification, while algorithms are a set of instructions that perform a specific task or solve a problem.

What is data structure?
A data structure is a way of organising and storing data in a computer program so that it can be accessed and manipulated efficiently. It defines a set of rules for how data is organised, how it is accessed, and how operations can be performed on it. Examples include arrays, linked lists, and trees.

What is an algorithm?
An algorithm is a set of instructions for solving a problem or performing a task in a computer program. It defines a series of steps or procedures that must be followed in order to achieve a desired outcome. Algorithms are used in a wide range of applications, from search engines to robotics.

Types of DSA
There are many types of Data Structures and Algorithms (DSA) including arrays, linked lists, stacks, queues, trees, graphs, hash tables, and sorting and searching algorithms. Each DSA has its own strengths and weaknesses and is suitable for different types of data processing and storage needs.

Applications of DS
Data Structures have a wide range of applications in computer science, including database management, algorithm design and analysis, operating systems, artificial intelligence, machine learning, and web development. They are used to store, organise, and manipulate large amounts of data efficiently and effectively, enabling faster and more accurate processing of information.

Topics covered:
00:00 Introduction & Agenda
00:37 What is Graph Traversal
01:13 Breadth First Traversal (Breadth First Search or BFS)
02:46 BFS Applications
03:56 Understanding BFS with example
10:45 Implementation of BFS (Code) in Java
17:46 Finding the shortest path from source node (Distance)
24:22 Finding shortest path from one node to another
27:13 Application of shortest path algorithm

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