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Grokking Coding Interview Patterns in C++

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level

Intermediate

Duration

85h

Lessons

439 Lessons

Master 24 essential coding interview patterns in C++ with 498 lessons and 540 exercises. Prepare for coding interviews with real-world examples and expert guidance.

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With thousands of potential questions to account for, preparing for the coding interview can feel like an impossible challenge. Yet with a strategic approach, coding interview prep doesn’t have to take more than a few weeks. Stop drilling endless sets of practice problems, and prepare more efficiently by learning coding interview patterns.

This course teaches you the underlying patterns behind common coding interview questions. By learning these essential patterns, you will be able to unpack and answer any problem the right way — just by assessing the problem statement. This approach was created by FAANG hiring managers to help you prepare for the typical rounds of interviews at major tech companies like Apple, Google, Meta, Microsoft, and Amazon.

Before long, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence.

This course is also available in JavaScript, Python, Go, and C++ — with more coming soon!

 

What You’ll Learn

 

  • Understand the essential patterns behind common coding interview questions — without having to drill endless problem sets
  • Identify the underlying pattern of each interview question by assessing the problem statement (and learn the tricks required to solve it)
  • Practice your skills in a hands-on, setup-free coding environment
  • Learn to efficiently evaluate the tradeoffs between time and space complexity in different solutions
  • Develop a flexible conceptual framework for solving any question, by connecting problem characteristics, solution techniques, and coding design patterns

Course Content

1.Getting Started

Get familiar with coding design patterns to excel in coding interviews.

  • Course Overview
  • Who Should Take This Course
  1. Two Pointers

Walk through the fundamentals of the two-pointers technique for solving various coding problems.

  • Introduction to Two Pointers
  • Valid Palindrome
  • Solution: Valid Palindrome
  • 3Sum
  • Solution: 3Sum
  • Remove Nth Node from End of List
  • Solution: Remove Nth Node from End of List
  • Sort Colors
  • Solution: Sort Colors
  • Reverse Words in a String
  • Solution: Reverse Words in a String
  • Valid Word Abbreviation
  • Solution: Valid Word Abbreviation
  • Strobogrammatic Number
  • Solution: Strobogrammatic Number
  • Minimum Number of Moves to Make Palindrome
  • Solution: Minimum Number of Moves to Make Palindrome
  • Next Palindrome Using Same Digits
  • Solution: Next Palindrome Using Same Digits
  • Lowest Common Ancestor of a Binary Tree III
  • Solution: Lowest Common Ancestor of a Binary Tree III
  • Valid Palindrome II
  1. Fast and Slow Pointers

Go hands-on with fast and slow pointers to detect cycles, middle nodes, and duplicates.

  • Introduction to Fast and Slow Pointers
  • Happy Number
  • Solution: Happy Number
  • Linked List Cycle
  • Solution: Linked List Cycle
  • Middle of the Linked List
  • Solution: Middle of the Linked List
  • Circular Array Loop
  • Solution: Circular Array Loop
  • Find the Duplicate Number
  • Solution: Find the Duplicate Number
  • Palindrome Linked List
  • Solution: Palindrome Linked List
  • Maximum Twin Sum of a Linked List
  • Solution: Maximum Twin Sum of a Linked List
  • Split a Circular Linked List
  • Solution: Split a Circular Linked List
  1. Sliding Window

Grasp the fundamentals of efficiently solving subarray and substring problems using the sliding window technique.

  • Introduction to Sliding Window
  • Repeated DNA Sequences
  • Solution: Repeated DNA Sequences
  • Sliding Window Maximum
  • Solution: Sliding Window Maximum
  • Minimum Window Subsequence
  • Solution: Minimum Window Subsequence
  • Longest Repeating Character Replacement
  • Solution: Longest Repeating Character Replacement
  • Minimum Window Substring
  • Solution: Minimum Window Substring
  • Longest Substring without Repeating Characters
  • Solution: Longest Substring without Repeating Characters
  • Minimum Size Subarray Sum
  • Solution: Minimum Size Subarray Sum
  • Maximum Average Subarray I
  • Solution: Maximum Average Subarray I
  • Diet Plan Performance
  • Solution: Diet Plan Performance
  • Best Time to Buy and Sell Stock
  1. Merge Intervals

Map out the steps for solving overlapping interval problems in various contexts.

  • Introduction to Merge Intervals
  • Merge Intervals
  • Solution: Merge Intervals
  • Insert Interval
  • Solution: Insert Interval
  • Interval List Intersections
  • Solution: Interval List Intersections
  • Employee Free Time
  • Solution: Employee Free Time
  • Task Scheduler
  • Solution: Task Scheduler
  • Meeting Rooms II
  1. In-Place Manipulation of a Linked List

Follow efficient in-place linked list manipulation techniques for various node reordering and removal tasks.

  • Introduction to In-Place Manipulation of a Linked List
  • Reverse Linked List
  • Solution: Reverse Linked List
  • Reverse Nodes in k-Group
  • Solution: Reverse Nodes in k-Group
  • Reverse Linked List II
  • Solution: Reverse Linked List II
  • Reorder List
  • Solution: Reorder List
  • Swapping Nodes in a Linked List
  • Solution: Swapping Nodes in a Linked List
  • Reverse Nodes in Even Length Groups
  • Solution: Reverse Nodes in Even Length Groups
  • Remove Duplicates from Sorted List
  • Solution: Remove Duplicates from Sorted List
  • Swap Nodes in Pairs
  1. Two Heaps

Build on efficient data structures and algorithms using two heaps for dynamic data processing.

  • Introduction to Two Heaps
  • IPO
  • Solution: IPO
  • Find Median from Data Stream
  • Solution: Find Median from Data Stream
  • Sliding Window Median
  • Solution: Sliding Window Median
  • Schedule Tasks on Minimum Machines
  • Solution: Schedule Tasks on Minimum Machines
  • Meeting Rooms III
  • Solution: Meeting Rooms III
  • Largest Number After Digit Swaps by Parity
  • Solution: Largest Number After Digit Swaps by Parity
  • Find Right Interval
  • Solution: Find Right Interval
  1. K-way merge

Step through the key techniques and algorithms for efficiently merging sorted data structures.

  • Introduction to K-way Merge
  • Merge Sorted Array
  • Solution: Merge Sorted Array
  • Kth Smallest Number in M Sorted Lists
  • Solution: Kth Smallest Number in M Sorted Lists
  • Find K Pairs with Smallest Sums
  • Solution: Find K Pairs with Smallest Sums
  • Merge K Sorted Lists
  • Solution: Merge K Sorted Lists
  • Kth Smallest Element in a Sorted Matrix
  • Solution: Kth Smallest Element in a Sorted Matrix
  1. Top K Elements

Unpack the core of identifying top K elements using heaps in various scenarios.

Introduction to Top K Elements

  • Kth Largest Element in a Stream
  • Solution: Kth Largest Element in a Stream
  • Reorganize String
  • Solution: Reorganize String
  • K Closest Points to Origin
  • Solution: K Closest Points to Origin
  • Top K Frequent Elements
  • Solution: Top K Frequent Elements
  • Kth Largest Element in an Array
  • Solution: Kth Largest Element in an Array
  • Third Maximum Number
  • Solution: Third Maximum Number
  • Find Subsequence of Length K with the Largest Sum
  • Solution: Find Subsequence of Length K with the Largest Sum
  • Minimum Cost to Hire K Workers
  • Solution: Minimum Cost to Hire K Workers
  1. Modified Binary Search

Break apart various search techniques using modified binary search for different problem scenarios.

  • Introduction to Modified Binary Search
  • Binary Search
  • Solution: Binary Search
  • Search in Rotated Sorted Array
  • Solution: Search in Rotated Sorted Array
  • First Bad Version
  • Solution: First Bad Version
  • Random Pick with Weight
  • Solution: Random Pick with Weight
  • Find K Closest Elements
  • Solution: Find K Closest Elements
  • Single Element in a Sorted Array
  • Solution: Single Element in a Sorted Array
  • Maximum Value at a Given Index in a Bounded Array
  • Solution: Maximum Value at a Given Index in a Bounded Array
  • The K Weakest Rows in a Matrix
  • Solution: The K Weakest Rows in a Matrix
  • Search in Rotated Sorted Array II
  1. Subsets

Grasp the fundamentals of subsets, permutations, letter combinations, balanced parentheses, and k-sum subsets.

  • Introduction to Subsets
  • Subsets
  • Solution: Subsets
  • Permutations
  • Solution: Permutations
  • Letter Combinations of a Phone Number
  • Solution: Letter Combinations of a Phone Number
  • Generate Parentheses
  • Solution: Generate Parentheses
  • Find K-Sum Subsets

12.Greedy Techniques

Dig deeper into the application and optimization of greedy algorithms across various problem scenarios.

  • Introduction to Greedy Techniques
  • Jump Game
  • Solution: Jump Game
  • Boats to Save People
  • Solution: Boats to Save People
  • Gas Station
  • Solution: Gas Station
  • Two City Scheduling
  • Solution: Two City Scheduling
  • Minimum Number of Refueling Stops
  • Solution: Minimum Number of Refueling Stops
  • Largest Palindromic Number
  • Solution: Largest Palindromic Number
  • Assign Cookies
  • Solution: Assign Cookies
  • Rearranging Fruits
  • Solution: Rearranging Fruits
  • Number of Steps to Reduce a Binary Number to One
  • Solution: Number of Steps to Reduce a Binary Number to One
  • Jump Game II

13.Backtracking

See how it works to solve problems using backtracking, from N-Queens to Sudoku.

  • Introduction to Backtracking
  • N-Queens
  • Solution: N-Queens
  • Word Search
  • Solution: Word Search
  • House Robber III
  • Solution: House Robber III
  • Restore IP Addresses
  • Solution: Restore IP Addresses
  • Flood Fill
  • Solution: Flood Fill
  • Minimum Moves to Spread Stones Over Grid
  • Solution: Minimum Moves to Spread Stones Over Grid
  • Binary Tree Paths
  • Solution: Binary Tree Paths
  • Sudoku Solver
  • Matchsticks to Square

14.Dynamic Programming

Master dynamic programming concepts, optimize solutions using memoization and tabulation for complex problems.

  • Introduction to Dynamic Programming
  • 0/1 Knapsack
  • Solution: 0/1 Knapsack
  • Coin Change
  • Solution: Coin Change
  • N-th Tribonacci Number
  • Solution: N-th Tribonacci Number
  • Partition Equal Subset Sum
  • Solution: Partition Equal Subset Sum
  • Counting Bits
  • Solution: Counting Bits
  • 01 Matrix
  • Solution: 01 Matrix
  • House Robber II
  • Solution: House Robber II
  • Maximum Product Subarray
  • Solution: Maximum Product Subarray
  • Combination Sum
  • Solution: Combination Sum
  • Word Break
  • Solution: Word Break
  • Palindromic Substrings
  • Solution: Palindromic Substrings
  • Longest Common Subsequence
  • Solution: Longest Common Subsequence
  • Word Break II
  • Solution: Word Break II
  • Decode Ways
  • Solution: Decode Ways
  • Count the Number of Good Subsequences
  • Solution: Count the Number of Good Subsequences
  • Climbing Stairs

15.Cyclic Sort

Break down cyclic sort for efficient in-place sorting and finding missing, duplicate integers.

  • Introduction to Cyclic Sort
  • Missing Number
  • Solution: Missing Number
  • First Missing Positive
  • Solution: First Missing Positive
  • Find the Corrupt Pair
  • Solution: Find the Corrupt Pair
  • Find the First K Missing Positive Numbers

16.Topological Sort

Discover the logic behind topological sorting to solve dependency-based challenges and tasks.

  • Introduction to Topological Sort
  • Compilation Order
  • Solution: Compilation Order
  • Alien Dictionary
  • Solution: Alien Dictionary
  • Verifying an Alien Dictionary
  • Solution: Verifying an Alien Dictionary
  • Course Schedule II
  • Solution: Course Schedule II
  • Course Schedule
  • Solution: Course Schedule
  • Build a Matrix with Conditions
  • Solution: Build a Matrix with Conditions
  • Longest Path With Different Adjacent Characters
  • Solution: Longest Path With Different Adjacent Characters
  • Find All Possible Recipes from Given Supplies

17.Matrices

Examine matrix operations, problem-solving methods, real-world applications, and algorithmic solutions for matrix traversal and transformations.

  • Introduction to Matrices
  • Set Matrix Zeroes
  • Solution: Set Matrix Zeroes
  • Rotate Image
  • Solution: Rotate Image
  • Spiral Matrix
  • Solution: Spiral Matrix
  • Where Will the Ball Fall
  • Solution: Where Will the Ball Fall
  • Transpose Matrix
  • Solution: Transpose Matrix
  • Count Negative Numbers in a Sorted Matrix
  • Solution: Count Negative Numbers in a Sorted Matrix
  • Minimum Time Takes to Reach Destination Without Drowning
  • Solution:Minimum Time Takes to Reach Destination Without Drowning
  • Smallest Rectangle Enclosing Black Pixels
  • Solution: Smallest Rectangle Enclosing Black Pixels

18.Stacks

Grasp the fundamentals of stacks, their operations, and applications in various problems.

  • Introduction to Stacks
  • Basic Calculator
  • Solution: Basic Calculator
  • Remove All Adjacent Duplicates In String
  • Solution: Remove All Adjacent Duplicates In String
  • Minimum Remove to Make Valid Parentheses
  • Solution: Minimum Remove to Make Valid Parentheses
  • Exclusive Time of Functions
  • Solution: Exclusive Time of Functions
  • Flatten Nested List Iterator
  • Solution: Flatten Nested List Iterator
  • Implement Queue Using Stacks
  • Solution: Implement Queue Using Stacks
  • Daily Temperatures
  • Solution: Daily Temperatures
  • Decode String
  • Solution: Decode String
  • Valid Parentheses

19.Graphs

Take a closer look at graph theory, algorithms, traversals, and solving various graph-related problems.

  • Introduction to Graphs
  • Network Delay Time
  • Solution: Network Delay Time
  • Paths in Maze That Lead to Same Room
  • Solution: Paths in Maze That Lead to Same Room
  • Clone Graph
  • Solution: Clone Graph
  • Graph Valid Tree
  • Solution: Graph Valid Tree
  • Bus Routes
  • Solution: Bus Routes
  • Reconstruct Itinerary
  • Solution: Reconstruct Itinerary
  • Find the Town Judge
  • Solution: Find the Town Judge
  • Find Center of Star Graph
  • Solution: Find Center of Star Graph

20.Tree Depth-First Search

See how it works to explore, transform, analyze, and optimize various binary tree operations.

  • Introduction to Tree Depth-First Search
  • Flatten Binary Tree to Linked List
  • Solution: Flatten Binary Tree to Linked List
  • Diameter of Binary Tree
  • Solution: Diameter of Binary Tree
  • Serialize and Deserialize Binary Tree
  • Solution: Serialize and Deserialize Binary Tree
  • Invert Binary Tree
  • Solution: Invert Binary Tree
  • Binary Tree Maximum Path Sum
  • Solution: Binary Tree Maximum Path Sum
  • Convert Sorted Array to Binary Search Tree
  • Solution: Convert Sorted Array to Binary Search Tree
  • Build Binary Tree from Preorder and Inorder Traversal
  • Solution: Build Binary Tree from Preorder and Inorder Traversal
  • Binary Tree Right Side View
  • Solution: Binary Tree Right Side View
  • Lowest Common Ancestor of a Binary Tree
  • Solution: Lowest Common Ancestor of a Binary Tree
  • Validate Binary Search Tree
  • Solution: Validate Binary Search Tree
  • Nested List Weight Sum II
  • Solution: Nested List Weight Sum II
  • Inorder Successor in BST
  • Solution: Inorder Successor in BST
  • Height of Binary Tree After Subtree Removal Queries
  • Solution: Height of Binary Tree After Subtree Removal Queries
  • Delete Nodes And Return Forest
  • Solution: Delete Nodes And Return Forest
  • Maximum Depth of Binary Tree
  • Kth Smallest Element in a BST

21.Tree Breadth-First Search

Build on performing efficient tree traversals with BFS approaches for various problems.

  • Introduction to Tree Breadth-First Search
  • Binary Tree Level Order Traversal
  • Solution: Binary Tree Level Order Traversal
  • Binary Tree Zigzag Level Order Traversal
  • Solution: Binary Tree Zigzag Level Order Traversal
  • Populating Next Right Pointers in Each Node
  • Solution: Populating Next Right Pointers in Each Node
  • Vertical Order Traversal of a Binary Tree
  • Solution: Vertical Order Traversal of a Binary Tree
  • Symmetric Tree
  • Solution: Symmetric Tree
  • Word Ladder
  • Solution: Word Ladder
  • Connect All Siblings of a Binary Tree

22.Trie

Step through efficiently managing strings with trie data structures and practical applications.

  • Introduction to Trie
  • Implement Trie (Prefix Tree)
  • Solution: Implement Trie (Prefix Tree)
  • Search Suggestions System
  • Solution: Search Suggestions System
  • Replace Words
  • Solution: Replace Words
  • Design Add and Search Words Data Structure
  • Solution: Design Add and Search Words Data Structure
  • Word Search II
  • Solution: Word Search II
  • Top K Frequent Words
  • Solution: Top K Frequent Words
  • Longest Common Prefix
  • Solution: Longest Common Prefix
  • Index Pairs of a String
  • Solution: Index Pairs of a String
  • Lexicographical Numbers

23.Hash Maps

Discover the logic behind designing hash maps, solving data structure challenges, and optimal algorithms.

  • Introduction to Hash Maps
  • Design HashMap
  • Solution: Design HashMap
  • Fraction to Recurring Decimal
  • Solution: Fraction to Recurring Decimal
  • Logger Rate Limiter
  • Solution: Logger Rate Limiter
  • Next Greater Element I
  • Solution: Next Greater Element I
  • Isomorphic Strings
  • Solution: Isomorphic Strings
  • Find Duplicate File in System
  • Solution: Find Duplicate File in System
  • Dot Product of Two Sparse Vectors
  • Solution: Dot Product of Two Sparse Vectors
  • High Five
  • Solution: High Five
  • Bulls and Cows
  • Solution: Bulls and Cows
  • Custom Sort String
  • Solution: Custom Sort String
  • Number of Distinct Islands
  • Solution: Number of Distinct Islands
  • Number of Wonderful Substrings
  • Solution: Number of Wonderful Substrings
  • Total Appeal of a String
  • Solution: Total Appeal of a String
  • Continuous Subarray Sum
  • Solution: Continuous Subarray Sum
  • Unique Number of Occurrences
  • Solution: Unique Number of Occurrences
  • Longest Palindrome

24.Knowing What to Track

Examine efficient data tracking patterns and solutions for frequency-related problems.

  • Introduction to Knowing What to Track
  • Palindrome Permutation
  • Solution: Palindrome Permutation
  • Valid Anagram
  • Solution: Valid Anagram
  • Design Tic-Tac-Toe
  • Solution: Design Tic-Tac-Toe
  • Group Anagrams
  • Solution: Group Anagrams
  • Maximum Frequency Stack
  • Solution: Maximum Frequency Stack
  • First Unique Character in a String
  • Solution: First Unique Character in a String
  • Find All Anagrams in a String
  • Solution: Find All Anagrams in a String
  • Longest Palindrome by Concatenating Two-Letter Words
  • Solution: Longest Palindrome by Concatenating Two-Letter Words
  • Rank Teams by Votes
  • Solution: Rank Teams by Votes
  • Pairs of Songs With Total Durations Divisible by 60
  • Solution: Pairs of Songs With Total Durations Divisible by 60
  • Minimum Number of Pushes to Type Word II
  • Solution: Minimum Number of Pushes to Type Word II
  • Ransom Note

25.Union Find

Grasp the fundamentals of the union-find algorithm and its applications in various graph problems.

  • Introduction to Union Find
  • Redundant Connection
  • Solution: Redundant Connection
  • Number of Islands
  • Solution: Number of Islands
  • Most Stones Removed with Same Row or Column
  • Solution: Most Stones Removed with Same Row or Column
  • Longest Consecutive Sequence
  • Solution: Longest Consecutive Sequence
  • Last Day Where You Can Still Cross
  • Solution: Last Day Where You Can Still Cross
  • Regions Cut by Slashes
  • Solution: Regions Cut by Slashes
  • Accounts Merge
  • Solution: Accounts Merge
  • Minimize Malware Spread
  • Solution: Minimize Malware Spread
  • Find if Path Exists in Graph
  • Solution: Find if Path Exists in Graph
  • The Skyline Problem
  • Solution: The Skyline Problem
  • Evaluate Division

26.Custom Data Structures

Dig into custom data structures for efficient, scalable solutions in complex coding challenges.

  • Introduction to Custom Data Structures
  • Snapshot Array
  • Solution: Snapshot Array
  • Time Based Key-Value Store
  • Solution: Time Based Key-Value Store
  • LRU Cache
  • Solution: LRU Cache
  • Insert Delete GetRandom O(1)
  • Solution: Insert Delete GetRandom O(1)
  • Min Stack
  • Solution: Min Stack
  • Range Module
  • Solution: Range Module
  • Shortest Word Distance II
  • Solution: Shortest Word Distance II
  • Design HashSet
  • Solution: Design HashSet
  • Max Stack
  • Solution: Max Stack
  • Moving Average from Data Stream
  • Solution: Moving Average from Data Stream
  • Two Sum III – Data structure design
  • Solution: Two Sum III – Data structure design
  • LFU Cache

27.Bitwise Manipulation

Simplify complex topics in bitwise manipulation for efficient problem-solving and optimization.

  • Introduction to Bitwise Manipulation
  • Find the Difference
  • Solution: Find the Difference
  • Complement of Base 10 Integer
  • Solution: Complement of Base 10 Integer
  • Flipping an Image
  • Solution: Flipping an Image
  • Single Number
  • Solution: Single Number
  • Single Number II
  • Solution: Single Number II
  • Encode and Decode Strings
  • Solution: Encode and Decode Strings
  • Sum of All Subset XOR Totals
  • Solution: Sum of All Subset XOR Totals
  • Find The K-th Lucky Number
  • Solution: Find The K-th Lucky Number
  • Minimum Number of K Consecutive Bit Flips
  • Solution: Minimum Number of K Consecutive Bit Flips
  • Find the Longest Substring Having Vowels in Even Counts
  • Solution: Find the Longest Substring Having Vowels in Even Counts
  • Reverse Bits

28.Challenge Yourself

Master the steps to tackle diverse coding problems, enhancing problem-solving skills and strategic thinking.

  • Challenge Yourself: Introduction
  • Shortest Bridge
  • Number of Connected Components in an Undirected Graph
  • Median of Two Sorted Arrays
  • Pacific Atlantic Water Flow
  • Contains Duplicate
  • Maximum Subarray
  • Two Sum
  • Find Minimum in Rotated Sorted Array
  • Non-overlapping Intervals
  • Meeting Rooms
  • Largest Rectangle in Histogram
  • Subtree of Another Tree
  • Sort List
  • Number of 1 Bits
  • Container with Most Water
  • Evaluate Reverse Polish Notation
  • 4Sum
  • Loud and Rich
  • Product of Array Except Self
  • Longest Increasing Subsequence
  • Sum of Two Integers
  • Majority Element
  • Unique Paths
  • Longest Palindromic Substring
  • Permutations II
  • Number of Provinces
  • Linked List Cycle II
  • Minimum Flips to Make the Binary String Alternate
  • Lemonade Change
  • House Robber
  • Find All Numbers Disappeared in an Array
  • Find All Duplicates in an Array
  • Same Tree
  • Design In-Memory File System
  • Design File System
  • Asteroid Collision
  • Rotting Oranges
  • Add Binary
  • Multiply Strings
  1. Conclusion

Learn how to use the course’s concepts for continued success in coding interviews.

 

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Grokking Coding Interview Patterns in C++
Grokking Coding Interview Patterns in C++
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