Categories: DSA Using C or C++

DSA Course Syllabus

Module 1: Introduction to DSA

  • What is DSA? Importance and Applications
  • Algorithm Analysis
    • Time and Space Complexity
    • Big-O, Big-Theta, Big-Omega Notations
  • Recursion
    • Concept and Applications
    • Recursive vs Iterative Approach
    • Practice Problems

Module 2: Arrays and Strings

  • One-dimensional and Two-dimensional Arrays
  • Operations: Traversal, Insertion, Deletion, Searching, Sorting
  • Multi-dimensional Arrays
  • Strings and String Operations
    • Reverse, Palindrome, Pattern Matching
  • Applications: Matrix Manipulation, Anagram Checker

Module 3: Linked Lists

  • Singly Linked List
    • Operations: Insertion, Deletion, Traversal
    • Applications: Implementing Stacks/Queues
  • Doubly Linked List
    • Operations and Use Cases
  • Circular Linked List
  • Applications: Dynamic Memory Allocation

Module 4: Stacks and Queues

  • Stack:
    • Push, Pop, Peek Operations
    • Applications: Expression Evaluation, Backtracking
  • Queue:
    • Enqueue, Dequeue, Circular Queues
    • Applications: Scheduling, Buffer Management
  • Priority Queues and Deques

Module 5: Trees

  • Introduction to Trees and Terminology (Root, Leaf, Height, etc.)
  • Binary Trees: Representation and Traversals (Inorder, Preorder, Postorder)
  • Binary Search Trees (BST)
    • Operations: Insertion, Deletion, Searching
    • Applications: Dictionary, Hierarchical Data
  • Balanced Trees (Overview)
    • AVL Trees, Red-Black Trees

Module 6: Graphs

  • Introduction to Graphs and Terminology (Vertices, Edges, Degree)
  • Representations: Adjacency Matrix, Adjacency List
  • Graph Traversals:
    • Depth First Search (DFS)
    • Breadth First Search (BFS)
  • Applications: Shortest Path, Connectivity

Module 7: Hashing

  • Hash Tables and Hash Functions
  • Collision Resolution Techniques
    • Chaining
    • Open Addressing
  • Applications: Caching, Indexing

Module 8: Sorting and Searching Algorithms

  • Searching:
    • Linear Search, Binary Search
  • Sorting:
    • Bubble Sort, Selection Sort, Insertion Sort
    • Merge Sort, Quick Sort, Heap Sort
  • Time and Space Complexity Comparison

Module 9: Advanced Topics

  • Heap:
    • Max-Heap and Min-Heap
    • Applications: Priority Queues, Heap Sort
  • Greedy Algorithms:
    • Activity Selection Problem, Huffman Coding
  • Divide and Conquer Algorithms:
    • Merge Sort, Quick Sort
  • Dynamic Programming:
    • Knapsack Problem, Longest Common Subsequence
  • Backtracking:
    • N-Queens Problem, Sudoku Solver

Module 10: Practice and Competitive Programming

  • Solving Real-Life Problems
  • Optimization Techniques
  • Tips for Competitive Programming
  • Mock Competitions

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