Mini Map
Search
⌘ K
AI Features
Log In
Grokking the Coding Interview Patterns in Python*
1.
Introduction
What Are Coding Patterns?
Why Do We Need Coding Patterns?
How to Identify the Right Pattern
Common Mistakes Learners Make
Prerequisites for This Course
2.
Two Pointers
Introduction to Two Pointers
Two Pointers: Intuition
Two Pointers: Pseudocode
When to Use the Two Pointers Pattern
Guess the Pattern 1
Guess the Pattern 2
Guess the Pattern 3
Valid Palindrome
Valid Palindrome: Solution Algorithm
Valid Palindrome: Algorithm Dry Run 1
Valid Palindrome: Algorithm Dry Run 2
Valid Palindrome: Algorithm Dry Run 3
Valid Palindrome: Solution Code
Valid Palindrome: Complexity Analysis
MCQ 1
MCQ 2
MCQ 3
Two Pointers: Practice Problems
Recap: Two Pointers
3.
Fast and Slow Pointers
Introduction to Fast and Slow Pointers
Fast and Slow Pointers: Intuition
Fast and Slow Pointers: Pseudocode
When to Use the Fast and Slow Pointers Pattern
Guess the Pattern 1
Guess the Pattern 2
Guess the Pattern 3
Linked List Cycle
Linked List Cycle: Solution Algorithm
Linked List Cycle: Algorithm Dry Run 1
Linked List Cycle: Algorithm Dry Run 2
Linked List Cycle: Algorithm Dry Run 3
Linked List Cycle: Algorithm Dry Run 4
Linked List Cycle: Solution Code
Linked List Cycle: Complexity Analysis
MCQ 1
MCQ 2
MCQ 3
Fast and Slow Pointers: Practice Problems
Recap: Fast and Slow Pointers
4.
Sliding Window
Introduction to Sliding Window
Sliding Window: Intuition
Sliding Window: Fixed vs Dynamic Window
When to Use the Sliding Window Pattern
Guess the Pattern 1
Guess the Pattern 2
Guess the Pattern 3
Minimum Size Subarray Sum
Minimum Size Subarray Sum: Solution Algorithm
Minimum Size Subarray Sum: Solution Code
Minimum Size Subarray Sum: Complexity Analysis
MCQ 1
MCQ 2
Sliding Window: Practice Problems
Recap: Sliding Window
5.
In-Place Manipulation of a Linked List
Introduction to In-Place Manipulation of a Linked List
In-Place Manipulation of a Linked List: Intuition
When to Use the In-place Manipulation of a Linked List Pattern
Guess the Pattern 1
Guess the Pattern 2
Reverse Linked List
Reverse Linked List: Solution Algorithm
Reverse Linked List: Algorithm Dry Run 1
Reverse Linked List: Algorithm Dry Run 2
Reverse Linked List: Algorithm Dry Run 3
Reverse Linked List: Algorithm Dry Run 4
Reverse Linked List: Algorithm Dry Run 5
Reverse Linked List: Algorithm Dry Run 6
Reverse Linked List: Solution Code
Reverse Linked List: Complexity Analysis
MCQ 1
MCQ 2
MCQ 3
In-Place Manipulation of a Linked List: Practice Problems
Recap: In-Place Manipulation of a Linked List
6.
Top K Elements
Introduction to Top K Elements
Top K Elements: Intuition
Top K Elements: Pseudocode
When to Use the Top K Elements Pattern
Guess the Pattern 1
Guess the Pattern 2
Guess the Pattern 3
Top K Frequent Elements
Top K Frequent Elements: Solution Algorithm
Top K Frequent Elements: Solution Code
Top K Frequent Elements: Complexity Analysis
MCQ 1
MCQ 2
MCQ 3
MCQ 4
Top K Elements: Practice Problems
Recap: Top K Elements
7.
Modified Binary Search
Introduction to Modified Binary Search
Modified Binary Search: Intuition
When to Use the Modified Binary Search Pattern
Guess the Pattern 1
Guess the Pattern 2
Guess the Pattern 3
Guess the Pattern 4
Search in Rotated Sorted Array
Search in Rotated Sorted Array: Solution Algorithm
Search in Rotated Sorted Array: Solution Code
Search in Rotated Sorted Array: Complexity Analysis
MCQ 1
MCQ 2
MCQ 3
Modified Binary Search: Practice Problems
Recap: Modified Binary Search
8.
Tree Depth-First Search
Introduction to Tree Depth-First Search
Tree Depth-First Search: Intuition
Tree Depth-First Search: Pseudocode
When to Use the Tree Depth-First Search Pattern
Guess the Pattern 1
Guess the Pattern 2
Maximum Depth of Binary Tree
Maximum Depth of Binary Tree: Solution Algorithm
Maximum Depth of Binary Tree: Algorithm Dry Run 1
Maximum Depth of Binary Tree: Algorithm Dry Run 2
Maximum Depth of Binary Tree: Algorithm Dry Run 3
Maximum Depth of Binary Tree: Algorithm Dry Run 4
Maximum Depth of Binary Tree: Algorithm Dry Run 5
Maximum Depth of Binary Tree: Solution Code
Maximum Depth of Binary Tree: Complexity Analysis
MCQ 1
MCQ 2
MCQ 3
MCQ 4
Tree Depth-First Search: Practice Problems
Recap: Tree Depth-First Search
9.
Dynamic Programming
Introduction to Dynamic Programming
Dynamic Programming: Intuition
Top-Down vs. Bottom-Up
When to Use the Dynamic Programming Pattern
Guess the Pattern 1
Guess the Pattern 2
Guess the Pattern 3
Maximum Product Subarray
Maximum Product Subarray: Solution Algorithm
Maximum Product Subarray: Dry Run 1
Maximum Product Subarray: Dry Run 2
Maximum Product Subarray: Dry Run 3
Maximum Product Subarray: Solution Code
Maximum Product Subarray: Complexity Analysis
MCQ 1
MCQ 2
MCQ 3
MCQ 4
Dynamic Programming: Practice Problems
Recap: Dynamic Programming
10.
Conclusion
You’re Building the Right Habits
This Isn’t the End — It’s the Beginning
Where to Go from Here
A Practical Pattern Selection Checklist
Common Mistakes Across All Patterns
How Interviewers Expect You to Use Patterns
How to Practice After This Course
Final Takeaway: Patterns as a Language
Claim your Certificate
Home
Courses
Grokking the Coding Interview Patterns in Python*
Top K Frequent Elements: Solution Algorithm
We'll cover the following...
This component is not supported in the current context
...