Data-Structure-And-Algorithms-using-Python

Welcome to the "30 Days of Data Structures and Algorithms using Python" repository! This repository contains a comprehensive 30-day plan for learning data structures and algorithms using the Python programming language.

Table of Contents

1. Day 1: Review the basics of Python programming

   • Data types
   • Control structures
   • Functions.

2. Day 2: Basic Data Structures in Python like List, Tuple

   • List Operations
   • Tuple Operations
   • Practice Problems

3. Day 3: Advanced Data Structures in Python like Dictionaries

   • Operations on Dictionary
   • Practice Problems

4. Day 4: Advanced Data Structures in Python like Set

   • Operations on Set
   • Practice Problems

5. Day 5: Basic complexity analysis and big-O notation

6. Day 6: Stacks and Queues

7. Day 7: Linked List and Its Types

8. Day 8: Operations on Linked List

9. Day 9: Sorting Algorithms like bubble sort, insertion sort, and selection sort

10. Day 10: Practice implementing and analyzing time and space complexity of Sorting Algorithms

11. Day 11: More Advanced Sorting algorithms like merge sort and quick sort

12. Day 12: Practice implementing and analyzing time and space complexity of sorting algorithms.

13. Day 13: Searching algorithms like linear search and binary search, and

14. Day 14: Practice implementing and analyzing the time and space complexity of Searching Algorithms

15. Day 15: Recursion and practice solving problems.

16. Day 16: Dynamic programming

17. Day 17: Practice solving problems using dynamic programming.

18. Day 18: Greedy algorithms

19. Day 19: Practice solving problems using greedy algorithms.

20. Day 20: Backtracking

21. Day 21: Trees

    • Binary Trees
    • Binary Search Trees

22. Day 22: Heaps

    • MinHeap
    • MaxHeap

23. Day 23: Graph data structures

    • Adjacency List
    • Adjacency matrix representations.

24. Day 24: Graph traversal algorithms

    • Depth-first search
    • Breadth-first search
    • Practice Problems

25. Day 25: Minimum Spanning Tree algorithms

    • Kruskal's algorithm
    • Prim's algorithm
    • Practice Problems

26. Day 26: Shortest path algorithms

    • Dijkstra's algorithm
    • Bellman-Ford algorithm
    • Practice Problems

27. Day 27: AVL trees

28. Day 28: Hash Tables

29. Day 29: Topological Sorting

30. Day 30: Revision and Conclusion

How to Use This Repository

This repository is organized by day, with each day containing a set of exercises and a corresponding solution in the form of a Jupyter notebook. To get the most out of this roadmap, we recommend that you follow the plan in order and try to complete the exercises on your own before looking at the solutions.

Prerequisites

• Python 3.x
• Jupyter Notebook

Contributing

We welcome contributions to this repository! If you have an idea for an exercise or a solution, please feel free to submit a pull request.

Acknowledgements

This roadmap is inspired by the "Cracking the Coding Interview" book and the "Data Structures and Algorithms in Python" course on Coursera.