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:
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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.
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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.
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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.
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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
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Toppers Bootcamp
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Rating Distribution
- 1 stars: 1 votes
- 2 stars: 4 votes
- 3 stars: 16 votes
- 4 stars: 40 votes
- 5 stars: 199 votes
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