# Data Structures & Algorithms in Python: Trees & Graphs

Python    |    Beginner
• 13 videos | 1h 32m 59s
• Includes Assessment
Rating 4.5 of 80 users (80)
This 13-video course explores the theory of graph and tree data structures in Python. Learners will examine a specific type of tree: the binary search tree, its structures and properties. You will then observe how to execute common tasks in binary tree; examine the binary search algorithm; and review data structures of linked lists, stacks, and queues. Next, learners will examine how a binary tree structure offers several applications that cannot be done by using stacks or queues. The course demonstrates different depth first traversals, including pre-order, in-order traversals, and post-order traversals. Explore graphs, which are data structures used to model relationships, and different representations of a graph, and learn to model a vertex. Learners continue by observing how to represent an adjacency list as a graph, and examining the adjacency matrix, the adjacency list, and the adjacency set. Then you will explore graph traversal algorithms, including the topological sort. Finally, learn how to traverse through each of the vertices in a graph.

## WHAT YOU WILL LEARN

• Discover the key concepts covered in this course
Describe how a sorted list of elements can be searched efficiently using a binary search
Recognize what trees and binary trees are and recall the properties of a binary search tree
Summarize how insert and lookup operations occur in a bst
Identify the minimum and maximum values in a bst, identify the greatest depth of the data structure, and calculate the sum of values from the root to a leaf node
Recall the different ways in which to traverse a bst and describe the method to perform a breadth first traversal
Summarize the pre-order and in-order depth first traversal techniques for a bst
• Describe the post-order traversal technique for a bst
Identify the components that make up a graph and recognize the different terms associated with these data structures
Recognize the different ways to represent graphs and describe the structure of an adjacency matrix
Summarize the representation of a graph in the form of an adjacency list and adjacency set
Traverse over the nodes in a graph using the topological sort algorithm
Summarize the properties of a binary search tree and list three different ways in which a graph can be represented

## IN THIS COURSE

• After completing this video, you will be able to describe how a sorted list of elements can be searched efficiently using binary search.
• 3.  The Binary Search Tree
After completing this video, you will be able to recognize what trees and binary trees are, and recall the properties of a binary search tree.
• 4.  BST: Insert and Lookup
In this video, you will summarize how insert and lookup operations occur in a binary search tree.
• 5.  BST: Extreme Values, Max Depth, and Sum Path
In this video, you will identify the minimum and maximum values in a BST, identify the greatest depth of the data structure, and calculate the sum of values from the root to a leaf node.
• 6.  BST: Breadth First Traversal
After completing this video, you will be able to recall the different ways to traverse a BST and describe the method to perform a breadth first traversal.
• 7.  BST: Depth First Traversal - Pre-Order and In-Order
In this video, you will learn how to summarize the pre-order and in-order depth first traversal techniques for a binary search tree.
• 8.  BST: Depth First Traversal - Post-Order
After completing this video, you will be able to describe the post-order traversal technique for a binary search tree.
• 9.  An Introduction to Graphs
In this video, you will identify the components that make up a graph and recognize the different terms associated with these data structures.
• 10.  Graphs as an Adjacency Matrix
After completing this video, you will be able to recognize the different ways to represent graphs and describe the structure of an adjacency matrix.
• 11.  Graphs as an Adjacency List and Set
In this video, learn how to summarize the representation of a graph in the form of an adjacency list and an adjacency set.
• 12.  The Topological Sort
In this video, find out how to traverse the nodes in a graph using the topological sort algorithm.
• 13.  Exercise: Trees and Graphs
During this video, you will learn how to summarize the properties of a binary search tree and list three different ways in which a graph can be represented.

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