Data Structures & Algorithms in Python: Trees & Graphs

Python 3.7
  • 13 Videos | 1h 38m 29s
  • Includes Assessment
  • Earns a Badge
Likes 72 Likes 72
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

  • Playable
    1. 
    Course Overview
    2m 16s
    UP NEXT
  • Playable
    2. 
    The Binary Search
    6m 6s
  • Locked
    3. 
    The Binary Search Tree
    9m 4s
  • Locked
    4. 
    BST: Insert and Lookup
    9m 36s
  • Locked
    5. 
    BST: Extreme Values, Max Depth, and Sum Path
    5m 29s
  • Locked
    6. 
    BST: Breadth First Traversal
    10m 51s
  • Locked
    7. 
    BST: Depth First Traversal - Pre-Order and In-Order
    7m 58s
  • Locked
    8. 
    BST: Depth First Traversal - Post-Order
    3m 31s
  • Locked
    9. 
    An Introduction to Graphs
    9m 36s
  • Locked
    10. 
    Graphs as an Adjacency Matrix
    6m 48s
  • Locked
    11. 
    Graphs as an Adjacency List and Set
    8m 11s
  • Locked
    12. 
    The Topological Sort
    8m 18s
  • Locked
    13. 
    Exercise: Trees and Graphs
    5m 15s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Likes 16 Likes 16  
Likes 47 Likes 47  

PEOPLE WHO VIEWED THIS ALSO VIEWED THESE