2024 Data Structures Using Python

2024 Data Structures Using Python, available at $49.99, has an average rating of 4.52, with 85 lectures, 5 quizzes, based on 260 reviews, and has 13002 subscribers.

You will learn about Beginner programmers: Those who have a basic understanding of Python and programming concepts but want to enhance their knowledge of data structures. Intermediate programmers: Individuals who are familiar with Python and have some experience with data structures but want to strengthen their understanding Computer science students: Students studying computer science or related fields who need to learn about data structures as part of their curriculum. Software developers: Professionals working in the software development industry who want to improve their understanding of data structures Self-learners: Individuals with a strong interest in programming and data structures who are motivated to learn on their own This course is ideal for individuals who are Beginner programmers or Intermediate programmers or Computer science students or Software developers or Self-learners It is particularly useful for Beginner programmers or Intermediate programmers or Computer science students or Software developers or Self-learners.

Enroll now: 2024 Data Structures Using Python

Summary

Title: 2024 Data Structures Using Python

Price: $49.99

Average Rating: 4.52

Number of Lectures: 85

Number of Quizzes: 5

Number of Published Lectures: 85

Number of Published Quizzes: 5

Number of Curriculum Items: 90

Number of Published Curriculum Objects: 90

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

Beginner programmers: Those who have a basic understanding of Python and programming concepts but want to enhance their knowledge of data structures.

Intermediate programmers: Individuals who are familiar with Python and have some experience with data structures but want to strengthen their understanding

Computer science students: Students studying computer science or related fields who need to learn about data structures as part of their curriculum.

Software developers: Professionals working in the software development industry who want to improve their understanding of data structures

Self-learners: Individuals with a strong interest in programming and data structures who are motivated to learn on their own

Who Should Attend

Beginner programmers

Intermediate programmers

Computer science students

Software developers

Self-learners

Target Audiences

Beginner programmers

Intermediate programmers

Computer science students

Software developers

Self-learners

Master Data Structures in Python: Unlock the Power of Efficient Programming!

Welcome to the most comprehensive and highly rated data structures course on Udemy! If you’re a student searching for a data structures course that will truly elevate your programming skills, look no further. This course is designed to provide you with the knowledge and expertise you need to excel in the world of data structures and algorithmic problem-solving.

In this course, we leave no stone unturned as we delve deep into the core concepts and practical implementations of essential data structures. From arrays and linked lists to stacks, queues, trees, and graphs, you’ll gain a solid foundation in each data structure and learn how to leverage their unique properties for optimal efficiency.

What sets this course apart? It’s simple. Our focus is on practicality and real-world applications. We understand that theory alone isn’t enough to excel as a programmer. That’s why we provide numerous hands-on coding exercises and projects that will put your newfound knowledge to the test. By solving real-world coding challenges, you’ll sharpen your problem-solving skills and develop the confidence to tackle complex programming tasks.

Here’s what you can expect from this course:

1. Comprehensive Coverage: We leave no stone unturned as we explore a wide range of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. You’ll learn the intricacies of each structure and gain a deep understanding of their strengths and weaknesses.

2. Hands-On Practice: Theory is important, but practice is crucial. Throughout the course, you’ll find an abundance of coding exercises and projects that will help solidify your understanding and hone your programming skills.

3. Real-World Applications: Data structures are not abstract concepts—they are tools that can solve real-world problems. We provide real-life examples and demonstrate how to apply each data structure to practical scenarios, ensuring that you can bridge the gap between theory and practice.

4. Expert Guidance: As an experienced instructor with a passion for teaching, I’ll guide you through every step of your learning journey. You can count on my support as you progress through the course, ensuring that you have a rich and rewarding learning experience.

By the end of this course, you’ll possess a deep understanding of data structures, algorithms, and their practical implementations. Armed with this knowledge, you’ll be well-equipped to tackle coding interviews, develop efficient software solutions, and excel in any programming challenge that comes your way.

Don’t miss out on the opportunity to become a Master of Data structures in Python. Enroll now, and let’s embark on this exciting journey together!

Happy Coding!!

Course Curriculum

Chapter 1: BONUS SECTION : Quck Review on Python Basics

Lecture 1: Variables

Lecture 2: Conditionals & If statement

Lecture 3: If statement example

Lecture 4: If else statement

Lecture 5: Example for If else statement

Lecture 6: Elif Statement

Lecture 7: Example for Elif Statement

Lecture 8: Nested if statement

Lecture 9: Example for Nested if statement

Lecture 10: While loop

Lecture 11: While loop to count the digits in a given number

Lecture 12: While loop to display multiplication table

Lecture 13: For loop

Lecture 14: Displaying numbers using for loop

Lecture 15: Break and Continue statement

Lecture 16: Finding Sum of first 10 numbers

Lecture 17: Finding Sum of digits in a given number

Chapter 2: Arrays in Python

Lecture 1: Definition

Lecture 2: Creating and Displaying 1D Arrays

Lecture 3: Accessing 1D Arrays

Lecture 4: Searching in 1D Arrays

Lecture 5: Insertion in 1D Arrays

Lecture 6: Deletion in 1D Arrays

Lecture 7: Updating in 1D Arrays

Lecture 8: Accessing 2D Arrays

Lecture 9: Insertion Operation in 2D Arrays

Lecture 10: Deletion Operation in 2D Arrays

Lecture 11: Update Operation in 2D Arrays

Chapter 3: Lists, Tuples, Sets and Dictionaries in Python

Lecture 1: Accessing Elements & Searching Element in a List

Lecture 2: Working with Operators on Lists

Lecture 3: Indexing and Slicing in Lists

Lecture 4: Working with List Methods

Lecture 5: List Comprehension

Lecture 6: Finding Maximum and Minimum Element in a List

Lecture 7: Tuples

Lecture 8: Tuple Indexing and Slicing

Lecture 9: Manipulating Tuples

Lecture 10: Unpacking Tuples

Lecture 11: Basics of Dictionary

Lecture 12: Accessing dictionary elements

Lecture 13: Working with dictionary

Lecture 14: Understanding Sets in Python

Chapter 4: Recursion

Lecture 1: Functions in python

Lecture 2: Example program1 on functions

Lecture 3: Example program2 on functions

Lecture 4: Example program3 on functions

Lecture 5: Recursion

Chapter 5: Linked Lists

Lecture 1: Basics of Linked lists

Lecture 2: Inserting an Element in a Linked List

Lecture 3: Searching an Element in a Linked List

Lecture 4: Finding Middle Element in a Linked List

Lecture 5: Checking whether two given Linked Lists are Identical or not ?

Lecture 6: Finding maximum value in a Linked list

Lecture 7: Deleting the Linked List

Chapter 6: Stacks

Lecture 1: Understanding Stacks

Lecture 2: Implementing Stacks in Python

Lecture 3: Implementing Stacks Using Lists with built-in methods in Python

Lecture 4: Implementing Stacks Using Collections-dequeue in Python

Lecture 5: Implementing Stacks Using Queue-Lifo Queue in Python

Lecture 6: Linked List Implementation of Stacks in Python

Lecture 7: Stack Application: Balanced Parenthesis

Lecture 8: Using Stacks for Checking Balanced Parenthesis

Chapter 7: Queues

Lecture 1: Understanding Queues

Lecture 2: Implementing Queues Using Lists with built-in methods in Python

Lecture 3: Implementing Queues Using Collections-dequeue in Python

Lecture 4: Implementing Queues using queue module in Python

Lecture 5: Implementing Queues Using LinkedLists

Lecture 6: Circular Queues

Chapter 8: Trees

Lecture 1: Tree Terminology

Lecture 2: Defining Binary Tree and Complete Binary Tree

Lecture 3: Representation of a Binary Tree

Lecture 4: Binary Tree Traversals

Lecture 5: How to Implement Inorder Traversal in Python ?

Lecture 6: How to Implement Pre-order Traversal in Python ?

Lecture 7: How to Implement Post-order Traversal in Python ?

Lecture 8: How to Implement Height of a Binary Tree in Python ?

Lecture 9: Sum of Elements in a Binary Tree

Chapter 9: Binary Search Trees

Lecture 1: Definition of BST with Example

Lecture 2: Search operation in BST

Lecture 3: Inserting a node in BST

Lecture 4: Creating a BST

Chapter 10: Graphs

Lecture 1: Basics of graphs

Lecture 2: Adjacency Matrix Representation

Lecture 3: Adjacency List Representation

Chapter 11: Coding Assessments

Instructors

Toppers Bootcamp
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Rating Distribution

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2 stars: 4 votes

3 stars: 16 votes

4 stars: 40 votes

5 stars: 199 votes

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