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About this course

Welcome to the Data Structures course using Python Programming language. This course covers all the different data structures through Python and gives you a deep and clear understanding that you will get benefitted while implementing these data structures in your own projects. Data structures are a very crucial part of computer science algorithms because they allow us to do data management efficiently and most Real projects need data structures implementation in them. This course covers 6 different modules and each module has different sections and subsections showing different data structures throughout the course. We implemented two projects named Knight travails and Tic Tac Toe in this course.

What You’ll Learn: 

  • Understand the importance of Data Structure in Programming
  • Know about the Python Basic built-in data structure 
  • Learn list data structures and its usage 
  • Able to implement arrays data structure in Python 
  • Able to understand the difference between list and Numpy arrays and implement arrays through Numpy Library 
  • Understand linked list data structure and its various operations using Python class and collections module 
  • Able to implement tree data structure and perform various operations on them. 
  • Able to implement graph data structure in python
  • Able to build the knight travails project using graph data structure.
  • Understand the importance of heaps and hashing in Python and their implementation 
  • Able to understand and build the Tic Tac Toe Game using Python Data Structure

  • Python
  • Data Structure
  • Data Structure Project
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  • 46%

    started a new career after completing these courses
  • 14%

    got a pay increase or promotion
  •   Flexible deadlines
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  •   Shareable Certificate
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  •   English

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Syllabus - What you will learn from this course



3 Hours to complete

Module 1: Python In-Built Data Structures

  • What is Python In-Built Data Structures ?
    • How does Data Structure help in Programming?
    • Python In-built Data Structure Introduction. Numbers
  • Numbers                  
    • Representation of Numbers
    • Integer, float and Complex numbers Strings
  • Strings                  
    • Characters and sequences of characters
    • Operations on strings
  • List and Tuple
    • Introduction to List Data Structures
    • Properties of List Data Structures
    • Tuples and sequences
    • Difference between List and Tuple
  • Set and Dictionaries
    • Set - Unordered Unique
    • Operations on sets
    • Dictionary - Key: Value Pair
    • Properties of Dictionary



3 Hours to complete

Module 2: Arrays

  • More on List
    • Using lists as stacks and queues
      • insert() and remove()
      • append() and pop()
    • List comprehensions
    • Nested List Comprehension
    • Lists as Dynamic Arrays
  • Arrays - Storing Same types
    • Importing array module
    • Basic Operations on array
  • Implementing Array using Numpy
    • What is Numpy ?
    • Why is NumPy Fast ?
    • Installing and importing Numpy
    • Array objects in Numpy
    • More on Numpy Arrays
  • Difference between Python List and Numpy Array
  • Searching and Sorting using arrays
  • Applications of Arrays



3 Hours to complete

Module 3: Linked Lists

  • Linked List In Python
    • Node, Data and Next in Linked Lists
    • Difference between lists and linked lists
    • Applications of Linked List
  • Collections.deque
    • Using deque submodule for linked list operations
    • append() and pop() operations
    • appendleft() and popleft() operations
    • Using deque for
      • Stacks
      • queues
  • Create our own linked lists using class
    • Class Node and class LinkedList
      • .next() and .join()
    • Traverse a Linked List
    • Insert and delete nodes
      • At beginning
      • At End
      • In-between two nodes
  • Doubly and Circular Linked List in Python
  • Applications of Linked List



4 Hours to complete

Module 4: Tree and Graphs

  • Tree Data Structure In Python
    • Root and Child Node in Tree
  • Binary Tree
    • Implementing Binary Tree in Python
      • Data, Pointer to left and right child
      • Construction of Binary Tree
    • Operations on Binary Trees
      • Traversal - Inorder, PreOrder and PostOrder
      • Checking and Printing in Binary Tree
    • Applications of Binary Tree
  • Binary Search Tree
    • Construction of BST in Python
    • Operations on BST
  • Trie Data Structure - Search Tree
    • Implementation of Trie Data Structure to search word
  • Graphs - Network of Nodes
    • Implementation of Graph in Python
      • Using Dictionary
        • Using an Adjacency list
        • Using an Adjacency Matrix
    • Searching in Graph
      • Using BFS
      • Using DFS
  • Topological Sorting
    • Implementation of DAG
  • Minimum Spanning Tree Implementation
    • Implement Prim’s and Kruskal Algorithm
  • Graph Application in Computer Science
  • “Knight Travails” Project



3 Hours to complete

Module 5: Heaps and Hashing Implementation

  • Implementing Heap Data Structure in Python
    • Types of Heap
      • Min and Max Heap
    • Implementation of Min and Max Heap using Class
      • Operations on Heap
        • Insert and Delete operations
        • Finding Minimum and Maximum elements
  • Hashing Technique - Associative Key/value Format
    • Python Dictionary implementation using hash table
    • Operations on Hashing
      • Insert and Delete Operations
    • Collision resolution in hashing
  • Applications of Heap and Hashing



2 Hours to complete

Module 6: Develop a Tic Tac Toe Game

  • Built a Tic Tac Toe Game on Jupyter Notebook
    • Display Board Function implementation
    • Player input function
    • Checking Marker
    • Completing the logic
  • Running Tic Tac Toe Game

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