📅 TRACK DAYS: 20 of 30

✅ COMPLETED ❌ NOT COMPLETED 🟠 IN-PROGRESS

Contents

• Data Structures and Algorithms
  • Introduction to Data Structures and Algorithms
    • Importance and Applications
    • Basic Definitions
    • Efficiency Analysis (Time and Space Complexity)
  • Fundamentals of Programming
    • Variables and Data Types
    • Control Structures (if, else, switch)
    • Loops (for, while, do-while)
  • Array and Strings
    • Arrays
    • Strings
    • Operations and Manipulations
  • Linked Lists
    • Singly Linked Lists
    • Doubly Linked Lists
    • Circular Linked Lists
    • Operations and Implementations
  • Stacks and Queues
    • Stack Operations
    • Queue Operations
    • Applications
  • Trees
    • Binary Trees
    • Binary Search Trees
    • AVL Trees
    • Heaps
    • Tree Traversals (In-order, Pre-order, Post-order)
  • Graphs
    • Graph Representation (Adjacency Matrix, Adjacency List)
    • Depth-First Search (DFS)
    • Breadth-First Search (BFS)
    • Shortest Path Algorithms (Dijkstra's, Bellman-Ford)
    • Minimum Spanning Tree (Prim's, Kruskal's)
  • Hashing
    • Hash Functions
    • Hash Tables
    • Collision Resolution
  • Sorting and Searching
    • Sorting Algorithms (Bubble, Selection, Insertion, Merge, Quick, Heap)
    • Searching Algorithms (Linear Search, Binary Search)
  • Dynamic Programming
    • Concept and Applications
    • Memoization and Tabulation
  • Divide and Conquer
    • Concept and Applications
    • Merge Sort, Quick Sort
  • Greedy Algorithms
    • Concept and Applications
    • Huffman Coding
  • Advanced Topics
    • Trie
    • Segment Tree
    • Disjoint Set (Union-Find)
  • Algorithmic Paradigms
    • Backtracking
    • Bit Manipulation
  • Complexity Classes
    • P, NP, NP-Complete
  • Case Studies and Real-world Applications
    • Application of DSA in Software Development
  • Interview Preparation
    • Commonly Asked DSA Questions
    • Problem-solving Strategies
  • Best Practices and Coding Standards
    • Code Optimization
    • Readable and Maintainable Code

📅 Days 1-5: Introduction to Data Structures

✅ Day 1: Introduction

• Importance and Applications
• Basic Definitions
• Time and Space Complexity

✅ Day 2-3: Stacks and Queues

• Learn about basic data structures: arrays, stacks, and queues.
• Implement and practice using stacks and queues.
• Solve problems involving these data structures.

✅ Day 4-5: Linked Lists

• Singly and doubly linked lists.
• Operations on linked lists.

📅 Days 6-12: Sorting and Searching Algorithms

✅ Day 6-9: Sorting Algorithms

• Bubble sort, selection sort, insertion sort.
• Quick sort, merge sort & Heap sort.

✅ Day 10-12: Searching Algorithms

• Linear search and binary search.
• Practice implementing and applying searching algorithms.

📅 Days 13-20: Trees and Graphs

✅ Day 13-15: Trees

• Binary trees, binary search trees (BST), AVL Tree, Heap.
• Tree traversal algorithms (in-order, pre-order, post-order).

✅ Day 16-17: Graphs

• Basics of graphs: representation and traversal.
• Depth-First Search (DFS) and Breadth-First Search (BFS).

✅ Day 18-19: Advanced Tree and Graph Concepts

• AVL trees, Red-Black trees.
• Advanced graph algorithms (Dijkstra's, Bellman-Ford, etc.).

📅 Days 20-25: Dynamic Programming

✅ Day 20: Introduction to Dynamic Programming (DP)

• Understanding the concept of overlapping sub-problems and optimal substructure.

❌ Day 21-25: Solve DP Problems

• Start with basic DP problems.
• Progress to more complex problems as you become comfortable.

📅 Days 26-30: Advanced Topics and Review

❌ Day 26-28: Advanced Data Structures

• Hashing, heaps, tries.
• Applications and use cases.

❌ Day 29: Advanced Algorithms

• Advanced sorting algorithms (e.g., heap sort).
• String matching algorithms.

❌ Day 30: Review and Reinforcement

• Go back to challenging problems and concepts.
• Mock interviews and real-world problem-solving.

© 30 DAYS OF DSA [ 2024-25 ]
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