Data Structures & Algorithms in Python: Trees & Graphs

Python    |    Beginner
  • 13 videos | 1h 32m 59s
  • Includes Assessment
  • Earns a Badge
Rating 4.5 of 80 users 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

  • 2m 16s
  • 6m 6s
    After completing this video, you will be able to describe how a sorted list of elements can be searched efficiently using binary search. FREE ACCESS
  • Locked
    3.  The Binary Search Tree
    9m 4s
    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. FREE ACCESS
  • Locked
    4.  BST: Insert and Lookup
    9m 36s
    In this video, you will summarize how insert and lookup operations occur in a binary search tree. FREE ACCESS
  • Locked
    5.  BST: Extreme Values, Max Depth, and Sum Path
    5m 29s
    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. FREE ACCESS
  • Locked
    6.  BST: Breadth First Traversal
    10m 51s
    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. FREE ACCESS
  • Locked
    7.  BST: Depth First Traversal - Pre-Order and In-Order
    7m 58s
    In this video, you will learn how to summarize the pre-order and in-order depth first traversal techniques for a binary search tree. FREE ACCESS
  • Locked
    8.  BST: Depth First Traversal - Post-Order
    3m 31s
    After completing this video, you will be able to describe the post-order traversal technique for a binary search tree. FREE ACCESS
  • Locked
    9.  An Introduction to Graphs
    9m 36s
    In this video, you will identify the components that make up a graph and recognize the different terms associated with these data structures. FREE ACCESS
  • Locked
    10.  Graphs as an Adjacency Matrix
    6m 48s
    After completing this video, you will be able to recognize the different ways to represent graphs and describe the structure of an adjacency matrix. FREE ACCESS
  • Locked
    11.  Graphs as an Adjacency List and Set
    8m 11s
    In this video, learn how to summarize the representation of a graph in the form of an adjacency list and an adjacency set. FREE ACCESS
  • Locked
    12.  The Topological Sort
    8m 18s
    In this video, find out how to traverse the nodes in a graph using the topological sort algorithm. FREE ACCESS
  • Locked
    13.  Exercise: Trees and Graphs
    5m 15s
    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. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Course Prompt Engineering to Learn Python Loops & Functions
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Course Graph Data Structures: Implementing Graph Traversal & Shortest Path Algorithms
Rating 4.6 of 16 users Rating 4.6 of 16 users (16)
Book Python for Engineering and Scientific Computing

PEOPLE WHO VIEWED THIS ALSO VIEWED THESE

Course Python Concurrent Programming: Introduction to Concurrent Programming
Rating 4.4 of 34 users Rating 4.4 of 34 users (34)
Course Leading in the Age of Generative AI
Rating 4.8 of 27 users Rating 4.8 of 27 users (27)
Course Getting Started with Python: Introduction
Rating 4.6 of 4247 users Rating 4.6 of 4247 users (4247)