Overview

Data Structures and Algorithms (DSA) form the backbone of efficient programming and problem-solving...

Why DSA Using Java?

Learning DSA with Java provides multiple benefits, including:

• A strong grasp of problem-solving techniques
• Efficient code optimization skills
• Understanding the underlying concepts of Java’s in-built data structures
• Preparation for competitive programming and technical interviews
• Applications in developing scalable and high-performing applications

Highlights

DSA Using Java Syllabus

• Introduction to Java:
  • Basics of Java Programming
  • Object-Oriented Programming Concepts
  • Java Collections Framework Overview
• Time and Space Complexity:
  • Understanding Big O Notation
  • Analyzing Algorithm Efficiency
  • Best, Average, and Worst Case Scenarios
• Array and Linked List:
  • Introduction to Arrays and Operations
  • Singly and Doubly Linked Lists
  • Circular Linked Lists
• Stacks and Queues:
  • Implementing Stacks Using Arrays and Linked Lists
  • Queue and Circular Queue Implementation
  • Priority Queues and Deques
• Hashing:
  • Hash Tables and Hash Functions
  • Collision Handling Techniques
  • Applications of Hashing
• Recursion:
  • Understanding Recursion
  • Recursive Functions and Problems
  • Backtracking Techniques
• Trees and Graphs:
  • Binary Trees and Binary Search Trees
  • Tree Traversals (Inorder, Preorder, Postorder)
  • Graph Representations and Traversals (DFS, BFS)
• Sorting and Searching:
  • Bubble Sort, Selection Sort, and Insertion Sort
  • Quick Sort and Merge Sort
  • Binary Search and Applications
• Dynamic Programming:
  • Introduction to DP and Memoization
  • Common DP Problems (Knapsack, Longest Common Subsequence)
  • Optimization Techniques
• Advanced Topics:
  • Segment Trees and Fenwick Trees
  • Trie Data Structure
  • Disjoint Set Union (Union-Find)