DSA - Data Structures and Algorithms

Course Description:

This comprehensive course on Data Structures and Algorithms is designed to build a solid foundation in problem-solving and programming logic. The course blends theory with hands-on practice, helping learners understand how data is organized, processed, and optimized. Ideal for software developers, engineering students, and professionals preparing for technical interviews, this course covers essential concepts using real-world examples and coding exercises in Java/Python/C++.

Course Content:

🔹 Module 1: Introduction

  • What are Algorithms and Data Structures?
  • Time and Space Complexity (Big O Notation)
  • Recursion vs Iteration
  • Asymptotic Analysis

🔹 Module 2: Arrays and Strings

  • Static vs Dynamic Arrays
  • Array Manipulation Techniques
  • 2D Arrays and Matrix Operations
  • String Manipulation and Pattern Matching
  • Sliding Window & Two Pointer Techniques

🔹 Module 3: Linked Lists

  • Singly and Doubly Linked Lists
  • Circular Linked Lists
  • Operations (Insertion, Deletion, Reversal)
  • Detecting Loops (Floyd’s Cycle Detection)

🔹 Module 4: Stacks and Queues

  • Stack Operations and Applications (Infix to Postfix, Balanced Parentheses)
  • Queue and Circular Queue
  • Priority Queue and Deque
  • Real-world Use Cases (Browser Back/Forward, Job Scheduling)

🔹 Module 5: Trees and Binary Trees

  • Binary Trees, Binary Search Trees (BST)
  • Tree Traversals (Inorder, Preorder, Postorder)
  • Balanced Trees (AVL, Red-Black Trees) – Intro
  • Lowest Common Ancestor, Diameter of Tree

🔹 Module 6: Heaps and Hashing

  • Min Heap and Max Heap
  • Heapify, Priority Queue Implementation
  • Hash Tables and Hash Maps
  • Collision Handling (Chaining, Open Addressing)

🔹 Module 7: Graphs

  • Representation (Adjacency Matrix & List)
  • Graph Traversal: DFS and BFS
  • Topological Sorting
  • Shortest Path (Dijkstra’s, Floyd-Warshall, Bellman-Ford)
  • Minimum Spanning Tree (Prim’s, Kruskal’s)

🔹 Module 8: Greedy Algorithms

  • Activity Selection Problem
  • Huffman Coding
  • Job Scheduling
  • Fractional Knapsack

🔹 Module 9: Divide and Conquer

  • Binary Search
  • Merge Sort, Quick Sort
  • Count Inversions
  • Closest Pair of Points

🔹 Module 10: Dynamic Programming

  • Memoization vs Tabulation
  • Fibonacci, Longest Common Subsequence
  • 0/1 Knapsack, Coin Change
  • Matrix Chain Multiplication

🔹 Module 11: Backtracking & Recursion

  • N-Queens Problem
  • Sudoku Solver
  • Subsets and Permutations
  • Rat in a Maze

🔹 Module 12: Interview Preparation & Problem Solving

  • Top 100 Coding Interview Questions
  • Code Debugging Practice
  • Daily Challenge Problems
  • Mock Tests and Coding Assessments

🎯 Learning Outcomes

🛠️ Tools Used: