Python Data Structures & Algorithms: Ace Coding Interviews
Python Data Structures & Algorithms: Ace Coding Interviews, available at $54.99, has an average rating of 4.54, with 143 lectures, 51 quizzes, based on 93 reviews, and has 13020 subscribers.
You will learn about Understand Data Structures and Algorithms & How to Implement and Use them in Python Understand Big O Notation and How to Calculate Space & Time Complexities Improve your Problem Solving Skills Enhance your Programming Skills Leetcode Challenges with Video Solutions Understand How to Decide When to Use a Specific Algorithm or Data Structure for Different Use Cases Ace Coding Interviews This course is ideal for individuals who are Python Programmers Who Want to Master Data Structures and Algorithms or Python Programmers Preparing for Coding Interviews or Python Programmers Who Want to Write More Efficient Code and Improve Their Problem-Solving Skills It is particularly useful for Python Programmers Who Want to Master Data Structures and Algorithms or Python Programmers Preparing for Coding Interviews or Python Programmers Who Want to Write More Efficient Code and Improve Their Problem-Solving Skills.
Enroll now: Python Data Structures & Algorithms: Ace Coding Interviews
Summary
Title: Python Data Structures & Algorithms: Ace Coding Interviews
Price: $54.99
Average Rating: 4.54
Number of Lectures: 143
Number of Quizzes: 51
Number of Published Lectures: 131
Number of Published Quizzes: 45
Number of Curriculum Items: 194
Number of Published Curriculum Objects: 176
Original Price: $94.99
Quality Status: approved
Status: Live
What You Will Learn
- Understand Data Structures and Algorithms & How to Implement and Use them in Python
- Understand Big O Notation and How to Calculate Space & Time Complexities
- Improve your Problem Solving Skills
- Enhance your Programming Skills
- Leetcode Challenges with Video Solutions
- Understand How to Decide When to Use a Specific Algorithm or Data Structure for Different Use Cases
- Ace Coding Interviews
Who Should Attend
- Python Programmers Who Want to Master Data Structures and Algorithms
- Python Programmers Preparing for Coding Interviews
- Python Programmers Who Want to Write More Efficient Code and Improve Their Problem-Solving Skills
Target Audiences
- Python Programmers Who Want to Master Data Structures and Algorithms
- Python Programmers Preparing for Coding Interviews
- Python Programmers Who Want to Write More Efficient Code and Improve Their Problem-Solving Skills
Welcome to the Data Structures and Algorithms in Python Course!
Are you a Python programmer who wants to write efficient code and improve your programming and problem solving skills ?
Do you have an upcoming coding interview and you want to ace it with confidence ?
If the answer is yes, then this course is the right choice for you!
In this course you will learn everything about Data Structures and Algorithms and how to implement and use them in Python.
The concepts are explained with animations which makes it much more easier to understand and memorize.
You will also apply your knowledge throughout the course via coding exercises and Leetcode coding challenges with video solutions.
The course covers the following topics:
General
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Why Should You Learn Data Structures and Algorithms ?
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What are Data Structures ?
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What are Algorithms ?
Big O Notation
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Linear Complexity – O(n)
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Constant Complexity – O(1)
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Quadratic Complexity – O(n^2)
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Logarithmic Complexity – O(logn)
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Constants in Big O
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Dominant and Non-Dominant Factors in Big O
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Complexities Comparison
Data Structures
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Linked Lists
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Doubly Linked Lists
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Stacks
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Queues
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Sets
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Trees
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Tries
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Heaps
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Hash Tables
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Graphs
Algorithms
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Linear Search
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Binary Search
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Bubble Sort
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Insertion Sort
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Selection Sort
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Merge Sort
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Recursion
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Tree Traversal
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Graph Traversal
I’m confident that you will enjoy this course, but if you for some reason are not happy with the course it’s backed by Udemy’s 30 day money back guarantee,so nothing to lose 🙂
I’m excited to see you in the course, hit that enroll button and start your mastering Data Structures & Algorithms journey 🙂
Course Curriculum
Chapter 1: Introduction
Lecture 1: Why Should You Learn Data Structures and Algorithms ?
Lecture 2: What are Data Structures ?
Lecture 3: What are Algorithms ?
Chapter 2: Big O Notation
Lecture 1: Introduction to Big O Notation
Lecture 2: Linear Complexity – O(n)
Lecture 3: Constant Complexity – O(1)
Lecture 4: Quadratic Complexity – O(n^2)
Lecture 5: Logarithmic Complexity – O(logn)
Lecture 6: Constants in Big O
Lecture 7: Dominant and Non-Dominant Factors in Big O
Lecture 8: Complexities Comparison
Chapter 3: Big O Notation: Practical
Chapter 4: Linked Lists
Lecture 1: Introduction to Linked Lists
Lecture 2: Linked List Class Implementation
Lecture 3: Linked List: Add Element
Lecture 4: Linked List: Append Implementation
Lecture 5: Linked List: Prepend Implementation
Lecture 6: Linked List: Iterating
Lecture 7: Linked List: Iterating Implementation
Lecture 8: Linked List: Removing Elements
Lecture 9: Linked List: Removing Elements Implementation
Lecture 10: Time Complexity of Linked Lists Operations
Lecture 11: When to Use Linked Lists
Lecture 12: Linked List Use Case: Shopping Cart
Chapter 5: Linked Lists: Practical
Lecture 1: Leetcode Challenge – Reverse Linked List: Solution
Lecture 2: Leetcode Challenge – Middle of the Linked List: Solution
Chapter 6: Doubly Linked Lists
Lecture 1: Introduction to Doubly Linked Lists
Lecture 2: Doubly Linked List Class Implementation
Lecture 3: Doubly Linked List: Append Implementation
Lecture 4: Doubly Linked List: Prepend Implementation
Lecture 5: Doubly Linked List: Delete Implementation
Lecture 6: Time Complexity of Doubly Linked Lists Operations
Lecture 7: Doubly Linked List Use Case: Text Cursor
Chapter 7: Doubly Linked Lists: Practical
Chapter 8: Stacks
Lecture 1: Introduction to Stacks
Lecture 2: Stack Implementation: Stack and Node Classes
Lecture 3: Stack Implementation: Push
Lecture 4: Stack Implementation: Pop & isEmpty
Lecture 5: Python Built-In List as Stack
Lecture 6: Stack Use Case: Text Editor Undo Functionality
Chapter 9: Stacks: Practical
Lecture 1: Leetcode Challenge – Valid Parentheses: Solution
Chapter 10: Queues
Lecture 1: Introduction to Queues
Lecture 2: Queue Implementation: Queue and Node Classes
Lecture 3: Queue Implementation: isEmpty
Lecture 4: Queue Implementation: Enqueue
Lecture 5: Queue Imeplementation: Dequeue
Lecture 6: Queue Use Case: Print Service
Chapter 11: Queues: Practical
Lecture 1: Leetcode Challenge – Implement Queue Using Two Stacks: Solution
Chapter 12: Sets
Lecture 1: Introduction to Sets
Lecture 2: Creating and Initializing Sets
Lecture 3: Set's Methods and Operations
Lecture 4: Sets Big O
Lecture 5: Set Use Case: Unique Words Count
Chapter 13: Sets Practical
Chapter 14: Trees
Lecture 1: Introduction to Trees
Lecture 2: Binary Trees
Lecture 3: Complete Binary Trees
Lecture 4: Binary Search Trees
Lecture 5: Binary Search Trees: Insert Operation
Lecture 6: Binary Search Trees: Class Implementation
Lecture 7: Binary Search Trees: Insert Operation Implementation
Lecture 8: Binary Search Trees: Search Operation Implementation
Chapter 15: Trees: Practical
Lecture 1: Leetcode Challenge – Search in a Binary Search Tree: Solution
Chapter 16: Heaps
Lecture 1: Introduction to Heaps
Lecture 2: Heaps: Insert
Lecture 3: Heaps: Pop
Lecture 4: Heap Implementation
Lecture 5: Heap Implementation: Insert & Heapify Up
Lecture 6: Heap Implementation: Pop
Lecture 7: Heap Implementation: Heapify Down
Lecture 8: Using heapq as Minimum Heap in Python
Lecture 9: Heap Operations Time Complexities
Instructors
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Ahmed Elsakka
Software Engineer
Rating Distribution
- 1 stars: 2 votes
- 2 stars: 1 votes
- 3 stars: 13 votes
- 4 stars: 30 votes
- 5 stars: 47 votes
Frequently Asked Questions
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