Data Structures 105-Day Super Advanced Study Roadmap

Week 1-2: Foundations of Python Programming

• Days 1-5: Introduction to Python syntax and basic data types
  • Python interpreter, variables, and data types
  • Basic operations and expressions
  • Control flow: if, else, and loops
• Days 6-10: Functions and modules
  • Function definition and parameters
  • Scope and lifetime of variables
  • Importing and using modules
• Days 11-14: Advanced Python features and best practices
  • List comprehensions and lambda functions
  • Error handling with try and except
  • Code organization and style (PEP 8)

Week 3-5: Arrays and Strings

• Days 15-20: Understanding arrays and their operations
  • One-dimensional arrays and multidimensional arrays
  • Array manipulation and slicing
• Days 21-25: String manipulation and algorithms
  • String operations and methods
  • Common string algorithms
• Days 26-30: Advanced array and string problems
  • Challenges involving arrays and strings
  • Optimizing solutions for better time and space complexity

Week 6-8: Linked Lists

• Days 31-35: Introduction to singly linked lists
  • Singly linked list structure and operations
  • Traversal, insertion, and deletion
• Days 36-40: Doubly linked lists and circular linked lists
  • Doubly linked list structure and operations
  • Circular linked list concepts and applications
• Days 41-45: Advanced linked list operations and optimization
  • Implementing complex algorithms with linked lists
  • Optimizing linked list operations for efficiency

Week 9-11: Stacks and Queues

• Days 46-50: Implementing stacks and basic operations
  • Stack implementation using arrays and linked lists
  • Basic stack operations: push, pop, peek
• Days 51-55: Queues and priority queues
  • Queue implementation and operations
  • Priority queue concepts and applications
• Days 56-60: Implementing advanced stack and queue applications
  • Designing algorithms using stacks and queues
  • Applications in solving real-world problems

Week 12-14: Trees

• Days 61-65: Introduction to binary trees
  • Binary tree structure and terminology
  • Traversal algorithms: in-order, pre-order, post-order
• Days 66-70: Binary search trees and AVL trees
  • Binary search tree properties and operations
  • Balancing with AVL trees
• Days 71-75: Heap and priority queues with trees
  • Heap structure and operations
  • Priority queue implementation using heaps

Week 15-17: Graphs

• Days 76-80: Graph representations and traversals
  • Introduction to graphs and their types
  • Adjacency matrix and adjacency list representation
  • Breadth-First Search (BFS) and Depth-First Search (DFS)
• Days 81-85: Shortest path algorithms
  • Dijkstra's algorithm
  • Bellman-Ford algorithm
  • Dynamic programming for shortest paths
• Days 86-90: Minimum spanning tree algorithms
  • Prim's algorithm
  • Kruskal's algorithm
  • Applications of minimum spanning trees

Week 18-20: Hashing

• Days 91-95: Understanding hash functions and collision resolution
  • Hash functions and their properties
  • Collision resolution techniques
• Days 96-100: Hash tables and applications
  • Implementing hash tables
  • Applications of hashing in real-world scenarios
• Days 101-105: Advanced hashing techniques and optimization
  • Perfect hashing
  • Cuckoo hashing
  • Optimizing hash functions for speed and minimal collisions

Remember to regularly practice coding exercises on platforms like LeetCode or HackerRank and work on mini-projects to solidify your understanding. Feel free to explore additional resources and dive deeper into specific areas that interest you.