Month 1: Foundations and Core Data Structures

Weeks 1-2: Arrays, Strings, and Hashing

• Topics to cover:
  • Arrays: Basics, Sliding Window, Two-pointer technique, Sorting algorithms.
  • Strings: Palindrome, Anagram, Pattern searching (KMP, Rabin-Karp).
  • Hashing: HashMap, HashSet, Counting frequency of elements, Hash functions.
• Practice Problems:
  • Two Sum, Maximum Subarray, Trapping Rain Water, Longest Substring Without Repeating Characters.
• Key Concepts:
  • Sorting (Merge Sort, Quick Sort).
  • Prefix Sum, Kadane’s Algorithm.

Weeks 3-4: Linked Lists, Stacks, and Queues

• Topics to cover:
  • Linked Lists: Single/Doubly Linked List, Fast and Slow pointers, Cycle detection.
  • Stacks and Queues: LRU Cache, Stack-based problems (Next Greater Element), Monotonic Stack.
• Practice Problems:
  • Linked List Cycle, Reverse Linked List, LRU Cache, Min Stack, Evaluate Reverse Polish Notation.
• Key Concepts:
  • Implementing basic operations (insertion, deletion, etc.).
  • Stack/Queue applications (e.g., in DFS, BFS).

Month 2: Recursion, Trees, and Graphs

Weeks 5-6: Recursion and Backtracking

• Topics to cover:
  • Recursion basics, Memoization.
  • Backtracking: Subsets, Permutations, N-Queens, Sudoku Solver.
• Practice Problems:
  • Subsets, Word Search, Generate Parentheses, Combination Sum.
• Key Concepts:
  • Recursive thinking.
  • Memoization vs. Tabulation (DP).

Weeks 7-8: Trees (Binary and BST)

• Topics to cover:
  • Binary Trees: Inorder, Preorder, Postorder traversal.
  • Binary Search Trees: Insertion, Deletion, Lowest Common Ancestor (LCA).
  • Tree problems: Depth-first search (DFS), Breadth-first search (BFS).
• Practice Problems:
  • Binary Tree Inorder Traversal, Binary Search Tree Iterator, Path Sum, Serialize and Deserialize Binary Tree.
• Key Concepts:
  • Tree traversal techniques (Iterative, Recursive).
  • Tree Depth/Height, Balanced Trees, AVL, Red-Black Trees (basic understanding).

Month 3: Advanced Topics and Dynamic Programming