Welcome to the Tree Data Structures section. This module covers everything from basic tree concepts to advanced algorithms, BST operations, and interview preparation.

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• Introduction to Trees — Definition, terminologies, properties
• Types of Trees — Binary Tree, BST, AVL, Red-Black, Full/Complete/Perfect
• Special Trees — Trie, Heap, Segment Tree

• Tree Representation — Pointer-based & array-based
• Time & Space Complexity — Performance analysis
• Tree Traversals — DFS (Inorder/Preorder/Postorder) & BFS

• Important Patterns — DFS recursion, BFS, LCA, Path Sum, Diameter
• BST Operations — Search, Insert, Delete, Balancing
• Heap Operations — Insert, Delete, Heapify

• Problem-Solving Approach — DFS vs BFS, recursive patterns
• Code Examples — Full implementations in JavaScript
• Interview Questions — Categorized LeetCode problems
• Tips & Common Mistakes — Expert advice and edge cases
• Real-World Applications — File systems, databases, autocomplete

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Step	Focus	Topic
1	Understand	Start with Introduction
2	Types	Learn Types of Trees
3	Representation	Study Pointer & Array representation
4	Traversals	Master DFS & BFS
5	Patterns	Practice Important Patterns
6	BST	Study BST Operations
7	Code	Study Code Examples
8	Practice	Solve Easy Interview Questions
9	Advanced	Special Trees & Hard problems

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• Recursion & Backtracking — Tree traversals are fundamentally recursive
• Graphs — Trees are a special case of graphs (acyclic, connected)
• Stack (LIFO) — Iterative DFS uses an explicit stack
• Queue (FIFO) — BFS traversal uses a queue