Data structures and algorithms are among the most fundamental concepts of Computer Science. Whether it’s real-world problems you’re trying to solve or the typical coding question asked in an interview, almost every problem requires you to demonstrate a deep understanding of data structures and algorithms. 

This course is a detailed review of some of the most common data structures and algorithms that you’ll see in interviews and your everyday work. With implementation details, thorough explanations, and hands-on coding exercises, you’ll quickly gain the confidence you need to solve any problem, no matter the situation.

Data Structures and Algorithms in Python

## Height of Tree
Let's start by defining the height of a tree. The height of a tree is the height of its root node. Now let's see what we mean by the height of a node:

### Height of Node
 
The height of a node is the number of edges on the longest path between that node and a leaf. The height of a leaf node is 0.

Recursively defined, the height of a node is one greater than the max of its right and left children’s height.

Below is an example of a binary tree labeled with heights of individual nodes: 

# Height of Tree
Let's start by defining the height of a tree. The height of a tree is the height of its root node. Now let's see what we mean by the height of a node:

## Height of Node
 
The height of a node is the number of edges on the longest path between that node and a leaf. The height of a leaf node is 0.

Recursively defined, the height of a node is one greater than the max of its right and left children’s height.

Below is an example of a binary tree labeled with heights of individual nodes: 

In this lesson, you will learn how to calculate the height of a binary tree. 

Introduction

Stack

Singly Linked Lists

Circular Linked Lists

Doubly Linked Lists

Arrays

Binary Trees

Binary Search Trees

Binary Search

Recursion

String Processing

Calculating the Height of a Binary Tree

Height of Tree

Height of Node