Description

Introduction of Data Structures & Algorithms(DS ALGO)

Data Structures & Algorithms(DS ALGO) are fundamental concepts in programming and software development. Data structures provide specialized formats for organizing and storing data, which allows for efficient access and modification; examples include arrays, linked lists, stacks, and trees, each tailored to specific application needs. Conversely, algorithms consist of step-by-step procedures for solving problems, encompassing everything from basic sorting and searching to more complex graph and optimization techniques. By mastering both data structures and algorithms, developers can create more efficient code, enhance performance, and optimize resource utilization. Therefore, a solid understanding of DS ALGO is crucial for success in software engineering, competitive programming, and technical interviews.

Prerequisites

1. Programming Knowledge
   • First, a solid foundation in languages like Python or Java is essential for understanding DS ALGO concepts.
2. Mathematical Fundamentals
   • Moreover, familiarity with basic math concepts and notation helps in evaluating the efficiency of algorithms.
3. Problem-Solving Skills
   • To succeed, developing strong problem-solving skills through practice, especially on platforms like LeetCode, is vital.
4. Software Development Principles
   • Lastly, understanding version control and using IDEs will significantly enhance the coding experience.

TABLE OF CONTENT

1.Introduction
1.1 Overview of Data Structures and Algorithms
1.2 Importance of DS & Algo in Computer Science

2.Basics of Programming
2.1 Programming Paradigms
2.2 Control Structures
2.3 Basic Data Types and Variables

3.Time and Space Complexity Analysis
3.1 Big-O Notation
3.2 Time Complexity Analysis (Ref: Data analysis in Power BI)
3.3 Space Complexity Analysis

4.Arrays
4.1 Introduction to Arrays
4.2 Array Operations
4.3 Multi-dimensional Arrays

5.Linked Lists
5.1 Singly Linked Lists
5.2 Doubly Linked Lists
5.3 Circular Linked Lists

6.Stacks
6.1 Introduction to Stacks
6.2 Stack Operations
6.3 Applications of Stacks

7.Queues
7.1 Introduction to Queues
7.2 Queue Operations
7.3 Types of Queues

8.Trees
8.1 Introduction to Trees
8.2 Binary Trees
8.3 Tree Traversal Techniques

9.Graphs
9.1 Introduction to Graphs
9.2 Types of Graphs
9.3 Graph Traversal Algorithms

10.Sorting Algorithms
10.1 Bubble Sort
10.2 Selection Sort
10.3 Insertion Sort
10.4 Merge Sort
10.5 Quick Sort

11.Searching Algorithms
11.1 Linear Search
11.2 Binary Search
11.3 Hashing

12.Hashing
12.1 Introduction to Hashing
12.2 Hash Functions
12.3 Hash Tables

13.Dynamic Programming
13.1 Introduction to Dynamic Programming
13.2 Memoization
13.3 Tabulation

14.Greedy Algorithms
14.1 Introduction to Greedy Algorithms
14.2 Greedy Choice Property
14.3 Applications of Greedy Algorithms

15.Advanced Data Structures
15.1 Priority Queues and Heaps
15.2 Disjoint Set (Union-Find) Data Structure
15.3 Trie Data Structure

1.Reference for Data Structure

2.Reference for Algorithms