In today’s DSA Tutorial, I’ve explained AVL Tree — the first self-balancing Binary Search Tree (BST) — in the simplest and most visual way possible with clear diagrams and real examples.

If you’ve ever wondered why BST becomes slow and unbalanced after inserting sorted data like 10, 20, 30, 40, 50 — this video is for you!

In this video, you will learn
* The problem with normal BST (when it becomes unbalanced)
* How an unbalanced BST behaves like a Linked List
* Why height of BST matters for performance
* What is an AVL Tree and how it maintains balance automatically
* Concept of Balance Factor (BF = Left Height - Right Height)
* Why valid balance factor range is {-1, 0, +1}
* Advantages of using AVL Tree — O(log n) search, insert & delete
* Real-life use cases of AVL Trees (like databases and indexing systems)
* Short intro of 4 rotation types (LL, RR, LR, RL) to fix imbalance
* Step-by-step diagram explanation of how AVL keeps the tree balanced

This is Part 1 of the AVL Tree series — here we focus on understanding the concept and logic behind balancing.
In the next video, we’ll discuss all 4 rotations of AVL Tree.

Perfect for beginners preparing for DSA interviews and coding placements.
All explanations are beginner-friendly and explained with visual clarity.

Subscribe to The Techzeen for upcoming hands-on AVL Tree rotation implementation video!

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