Data Structures and Algorithms (DSA) using JavaScript

1. Introduction to DSA

• What are Data Structures and Algorithms?
• Why are DSA important in programming?
• How DSA helps in solving real-world problems.
• Overview of Big-O notation (Time and Space Complexity).

2. Data Structures

• Arrays
  • Introduction to arrays and array operations (push, pop, shift, unshift, etc.).
  • Common problems: Reverse an array, find the maximum/minimum element, etc.
• Strings
  • String manipulations and methods in JavaScript.
  • Common problems: Palindrome check, anagram check, substring search.
• Linked Lists
  • Singly linked list: Creation, insertion, deletion.
  • Common problems: Reverse a linked list, detect cycles in a linked list.
• Stacks
  • Stack implementation using arrays or linked lists.
  • Applications: Validating parentheses, reversing strings.
• Queues
  • Queue implementation using arrays or linked lists.
  • Applications: Task scheduling, breadth-first search (BFS).
• Hashing
  • Introduction to hash tables (objects and Maps in JavaScript).
  • Common problems: Find duplicates, two-sum problem.
• Trees
  • Binary trees and Binary Search Trees (BST).
  • Tree traversal methods: In-order, Pre-order, Post-order.
  • Common problems: Height of a tree, level-order traversal.
• Graphs
  • Introduction to graphs: Adjacency matrix and list representation.
  • Depth-first search (DFS) and Breadth-first search (BFS) algorithms.
• Heaps
  • Introduction to heaps and priority queues.
  • Applications: Implementing heaps in JavaScript, heap sort.

3. Algorithms

• Sorting Algorithms
  • Bubble Sort, Selection Sort, Insertion Sort, Merge Sort, Quick Sort.
  • Time complexity comparison and use cases.
• Search Algorithms
  • Linear search and Binary search.
  • Common problems: Search in a sorted array, find the first/last occurrence of an element.
• Recursion
  • Understanding recursion and solving problems using recursive approaches.
  • Common problems: Fibonacci sequence, factorial, towers of Hanoi.