A **balanced tree**, specifically a balanced Binary Search Tree (BST), is a tree data structure in which the **heights of any node's left and right subtrees differ by at most one**. This balance ensures efficient searching, insertion, and deletion operations, maintaining a logarithmic time complexity for these operations. In a balanced BST, the tree's height is minimized, leading to optimal performance.    
Let's look at the example of **unbalanced tree**: 

In the provided BST, the left subtree of the root node has a height of `4`, while the right subtree has a height of only `2`. This **significant difference** in heights indicates that the tree is unbalanced, leading to inefficient search, insertion, and deletion operations compared to a balanced BST.

The understanding of data structures and algorithms: this is what sets advanced professionals apart from the rest. In the modern world of growing data, it is very important to be able to process large amounts of data efficiently. 

In this course, you will study the most basic data structures that help us to deal with huge amounts of data as well as implement the most basic and crucial concepts on your own so you’ll get a deeper understanding of how each data structure works and you'll be able to decide what data structure best suited for your task.

When we start learning something new, it is very important to get familiar with the subject of our study first. So let's dive deeper into what we will learn about in this course.

Arrays and lists serve as foundational data structures in programming, with Python employing them extensively. This section provides an overview of these structures, delving into their concepts and highlighting their implementation nuances within the Python programming language.

There are many applied tasks in which it is necessary to operate with large amounts of structured data and simple data structures such as an array or a linked list may no longer be enough for these purposes. In this section, we'll look at the concept of an abstract data type and how different ADTs allow us to efficiently manage large amounts of data.

In the real world, one often has to deal with tasks in which it is necessary to model complex dependencies between various nodes of a system or domain. Graphs can help us with this. In this section, we will learn what a graph is and how to represent it in computer memory efficiently.

Challenge: Balanced Trees

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