Data Structures in Python Online Course

Data Structures in Python Online Course

This course takes you from basic to advanced data structures, starting with arrays and lists, then progressing to linked lists, stacks, queues, trees, and graphs. You’ll learn both the theoretical aspects and practical implementations in Python, focusing on real-world applications. With video tutorials and hands-on exercises, you’ll develop the skills to optimize software performance and solve programming challenges efficiently. By the end, you'll be proficient in handling complex data structures and prepared to tackle real-world programming problems, making you a valuable asset in the tech industry.

Who is this book for?

This course is ideal for beginner to intermediate programmers, computer science students, and self-learners who are familiar with Python basics, such as variables, data types, loops, conditionals, and functions. It’s designed for those looking to advance their skills and dive into more complex data structures. Perfect for software developers and anyone eager to enhance their programming knowledge through a structured learning path.

What you will learn

• Define and manipulate various data structures in Python.
• Implement arrays, lists, tuples, and dictionaries for efficient data handling.
• Master complex data structures like linked lists, stacks, queues, and trees.
• Develop proficiency in graph theory and binary search trees.
• Utilize recursion for elegant and powerful code solutions.
• Apply data structures to solve common programming challenges.

Course Table of Contents

Arrays in Python

• Definition
• Creating and Displaying 1D Arrays
• Accessing 1D Arrays
• Searching in 1D Arrays
• Insertion in 1D Arrays
• Deletion in 1D Arrays
• Updating in 1D Arrays
• Accessing 2D Arrays
• Insertion Operation in 2D Arrays
• Deletion Operation in 2D Arrays
• Update Operation in 2D Arrays

Lists, Tuples, Sets, and Dictionaries in Python

• Accessing Elements & Searching Element in a List
• Working with Operators on Lists
• Indexing and Slicing in Lists
• Working with List Methods
• Append()
• Clear()
• count()
• extend()
• index()
• insert()
• pop()
• remove()
• reverse()
• sort()
• List Comprehension
• Finding Maximum and Minimum Element in a List
• Tuples
• Tuple Indexing and Slicing
• Manipulating Tuples
• Unpacking Tuples
• Basics of Dictionary
• Accessing dictionary elements
• Working with dictionary
• Understanding Sets in Python

Recursion

• Functions in Python
• Example Program1 on Functions
• Example Program2 on Functions
• Example Program3 on Functions
• Recursion

Linked Lists

• Basics of Linked Lists
• Inserting an Element in a Linked List
• Searching an Element in a Linked List
• Finding Middle Element in a Linked List
• Checking Whether Two Given Linked Lists are Identical or Not
• Finding Maximum Value in a Linked List
• Deleting the Linked List

Stacks

• Understanding Stacks
• Implementing Stacks in Python
• Implementing Stacks Using Lists with Built-in Methods in Python
• Implementing Stacks Using Collections-dequeue in Python
• Implementing Stacks Using Queue-LifoQueue in Python
• Linked List Implementation of Stacks in Python
• Stack Application: Balanced Parenthesis
• Using Stacks for Checking Balanced Parenthesis

Queues

• Understanding Queues
• Implementing Queues Using Lists with Built-in Methods in Python
• Implementing Queues Using Collections-dequeue in Python
• Implementing Queues Using Queue Module in Python
• Implementing Queues Using LinkedLists
• Circular Queues

Trees

• Tree Terminology
• Defining Binary Tree and Complete Binary Tree
• Representation of a Binary Tree
• Binary Tree Traversals
• How to Implement Inorder Traversal in Python?
• How to Implement Pre-order Traversal in Python?
• How to Implement Post-order Traversal in Python?
• How to Implement Height of a Binary Tree in Python?
• Sum of Elements in a Binary Tree

Binary Search Trees

• Definition of BST with Example
• Search Operation in BST
• Inserting a Node in BST
• Creating a BST

Graphs

• Basics of Graphs
• Adjacency Matrix Representation
• Adjacency List Representation