Data Structure and Algorithm

About Course

This comprehensive course delves into the fundamental concepts and advanced techniques of data structures and algorithms, essential for efficient data management and problem-solving in computer science. Beginning with an introduction to linear data structures like arrays, linked lists, stacks, and queues, the course progresses to nonlinear data structures, including trees and graphs, which facilitate complex data organization. Students will explore various sorting and searching algorithms to enhance data retrieval performance and understand hashing techniques for quick data access. Additionally, the course covers file structures, enabling efficient data storage and manipulation, preparing students for real-world applications and advanced studies in computer science.

In this course, students will explore the essential concepts and practical applications of data structures and algorithms, crucial for efficient data management and problem-solving in computer science. The curriculum covers linear data structures like arrays, linked lists, stacks, and queues, as well as nonlinear structures such as trees and graphs. Students will learn various sorting and searching algorithms to enhance data retrieval, delve into hashing techniques for quick data access, and understand file structures for efficient data storage and manipulation. By mastering these topics, students will be well-equipped to tackle real-world computational challenges and advance in their studies and careers in computer science.

Course Content

Introduction of DSA
This Topic introduces basic terminologies and concepts in data structures, covering elementary data organizations, operations like insertion, deletion, and traversal, data management principles, and types of data structures, including primitive and non-primitive data types.

Introduction

03:36
Introduction of DSA

Stack
This course section covers stack definitions and concepts, stack operations, and applications such as Polish and Reverse Polish expressions and their compilation. It also includes recursion techniques and the Tower of Hanoi problem.

Sorting and Searching
This part of the course explores various sorting algorithms including Insertion Sort, Bubble Sort, Selection Sort, Quick Sort, Merge Sort, and Heap Sort, as well as search algorithms like Linear Search and Binary Search, discussing their implementations, efficiencies, and applications in data processing and problem-solving.

Hashing
In this section, we delve into hashing, covering topics such as symbol tables, hashing functions for efficient data retrieval, and collision-resolution techniques to handle hash collisions effectively.

File Structure
This segment of the course introduces file structures, including the concepts of fields, records, and files. It covers sequential, indexed, and relative/random file organization methods, discusses indexing structures for index files, hashing for direct files, multi-key file organization, and various access methods for efficient data storage and retrieval.

Graph
This course section focuses on graph theory, covering matrix representation of graphs, elementary graph operations such as Breadth-First Search (BFS), Depth-First Search (DFS), spanning trees, shortest paths, and minimal spanning trees.

Tree
This course module explores trees, including definitions and concepts, binary tree representation, binary tree traversal methods (inorder, postorder, preorder), threaded binary trees, binary search trees, conversion of general trees to binary trees, and applications of trees such as AVL trees, 2-3 trees, height-balanced, weight-balanced trees, and B-trees.

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About Course

What Will You Learn?

Course Content

Introduction of DSA This Topic introduces basic terminologies and concepts in data structures, covering elementary data organizations, operations like insertion, deletion, and traversal, data management principles, and types of data structures, including primitive and non-primitive data types.

Introduction

Introduction of DSA

Stack This course section covers stack definitions and concepts, stack operations, and applications such as Polish and Reverse Polish expressions and their compilation. It also includes recursion techniques and the Tower of Hanoi problem.

Stack

Tower of Haino

Expression Evaluation

Stack

Sorting and Insertion Sort

Selection Sort

Quick Sort

Merge Sort

Bubble Sort

Linear Search

Binary Search

Sorting and Searching

Hashing In this section, we delve into hashing, covering topics such as symbol tables, hashing functions for efficient data retrieval, and collision-resolution techniques to handle hash collisions effectively.

Hashing

Collision

Collision Resolution

Hashing

File Structure

File Structure

Graph This course section focuses on graph theory, covering matrix representation of graphs, elementary graph operations such as Breadth-First Search (BFS), Depth-First Search (DFS), spanning trees, shortest paths, and minimal spanning trees.

Graph

BFS

DFS

Spanning Tree

Prim’s Algorithm

Kruskal’s Algorithm

Graph

Introduction of Tree

Binary Tree

Storage Representation of Binary Tree

Traversal of Binary Tree

Thread Binary Tree

Binary Search Tree

2-3 Tree

B – Tree

Tree

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Popular Contain

Introduction of DSA
This Topic introduces basic terminologies and concepts in data structures, covering elementary data organizations, operations like insertion, deletion, and traversal, data management principles, and types of data structures, including primitive and non-primitive data types.

Stack
This course section covers stack definitions and concepts, stack operations, and applications such as Polish and Reverse Polish expressions and their compilation. It also includes recursion techniques and the Tower of Hanoi problem.

Hashing
In this section, we delve into hashing, covering topics such as symbol tables, hashing functions for efficient data retrieval, and collision-resolution techniques to handle hash collisions effectively.

Graph
This course section focuses on graph theory, covering matrix representation of graphs, elementary graph operations such as Breadth-First Search (BFS), Depth-First Search (DFS), spanning trees, shortest paths, and minimal spanning trees.