HomeCoursesGrokking the Coding Interview Patterns in Go

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Grokking the Coding Interview Patterns in Go
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Grokking the Coding Interview Patterns in Go helps you prep faster with strategies developed by FAANG engineers. Learn essential patterns to confidently tackle interview questions from top companies.
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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, C++, Java, and Python — with more coming soon!
With thousands of potential questions to account for, preparing for the coding interview can feel like an impossible challenge. ...Show More

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
Understand the essential patterns behind common coding interview questions — without having to drill endless problem sets

Show more

Content

699 Lessons368 Quizzes365 Challenges

1.

Getting Started

2 Lessons

Get familiar with coding patterns to excel in solving coding interview challenges.
Course Overview
Who Should Take This Course

2.

Two Pointers

24 Lessons

Unpack the core of using two pointers for efficient data traversal and problem-solving.
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
Count Pairs Whose Sum is Less than Target
Solution: Count Pairs Whose Sum is Less than Target
Valid Palindrome II

4.

Sliding Window

25 Lessons

Enhance your skills in solving coding 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
Fruit Into Baskets
Solution: Fruit Into Baskets
Contains Duplicate II
Solution: Contains Duplicate II
Frequency of the Most Frequent Element
Solution: Frequency of the Most Frequent Element

6.

In-Place Manipulation of a Linked List

24 Lessons

Streamline linked list manipulation tasks like reversing segments, swapping nodes, and removing duplicates efficiently in-place.
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
Remove Linked List Elements
Solution: Remove Linked List Elements
Split Linked List in Parts
Solution: Split Linked List in Parts
Delete N Nodes After M Nodes of a Linked List
Solution: Delete N Nodes After M Nodes of a Linked List
Insert into a Sorted Circular Linked List
Solution: Insert into a Sorted Circular Linked List
Swap Nodes in Pairs

7.

Heaps

23 Lessons

Master the steps to apply heaps for dynamic data processing, maximizing profits, and efficient scheduling.
Introduction to 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
Minimum Cost to Connect Sticks
Solution: Minimum Cost to Connect Sticks
Longest Happy String
Solution: Longest Happy String
Maximum Average Pass Ratio
Solution: Maximum Average Pass Ratio
The Number of the Smallest Unoccupied Chair
Solution: The Number of the Smallest Unoccupied Chair

9.

Top K Elements

21 Lessons

Walk through efficient extraction of top-k elements in diverse real-world 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
Maximal Score After Applying K Operations
Solution: Maximal Score After Applying K Operations
Find the Kth Largest Integer in the Array
Solution: Find the Kth Largest Integer in the Array

12.

Greedy Techniques

27 Lessons

Take a closer look at greedy algorithms, implementing solutions in various optimization problems.
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
Maximum Swap
Solution: Maximum Swap
Can Place Flowers
Solution: Can Place Flowers
Largest Odd Number in String
Solution: Largest Odd Number in String
Jump Game II
Best Time to Buy and Sell Stock

14.

Dynamic Programming

32 Lessons

Master dynamic programming techniques with practical applications, optimizing complex problems through memoization and tabulation.
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

17.

Sort and Search

27 Lessons

Solve problems by organizing data through sorting and applying binary search, two-pointer, and sliding window for efficient solutions.
Introduction to Sort and Search
Find the Distance Value Between Two Arrays
Solution: Find the Distance Value Between Two Arrays
Longest Subsequence With Limited Sum
Solution: Longest Subsequence With Limited Sum
Find Target Indices After Sorting Array
Solution: Find Target Indices After Sorting Array
Count Pairs in Two Arrays
Solution: Count Pairs in Two Arrays
Valid Triangle Number
Solution: Valid Triangle Number
Minimum Operations to Make All Array Elements Equal
Solution: Minimum Operations to Make All Array Elements Equal
Sum of Mutated Array Closest to Target
Solution: Sum of Mutated Array Closest to Target
Range Sum of Sorted Subarray Sums
Solution: Range Sum of Sorted Subarray Sums
Magnetic Force Between Two Balls
Solution: Magnetic Force Between Two Balls
Find K-th Smallest Pair Distance
Solution: Find K-th Smallest Pair Distance
Minimum Space Wasted from Packaging
Solution: Minimum Space Wasted from Packaging
Russian Doll Envelopes
Solution: Russian Doll Envelopes
Two Sum Less Than K
Maximum Number of Integers to Choose from a Range I

18.

Matrices

25 Lessons

Examine key matrix operations, transformations, and algorithmic solutions for practical problems.
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
Island Perimeter
Solution: Island Perimeter
Convert 1D Array Into 2D Array
Solution: Convert 1D Array Into 2D Array
Spiral Matrix II
Solution: Spiral Matrix II
Flip Columns For Maximum Number of Equal Rows
Solution: Flip Columns For Maximum Number of Equal Rows
Number of Spaces Cleaning Robot Cleaned
Solution: Number of Spaces Cleaning Robot Cleaned

20.

Graphs

25 Lessons

Dig deeper into graph algorithms, covering traversal methods, shortest paths, cycles, and graph validation.
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
Lucky Numbers in a Matrix
Solution: Lucky Numbers in a Matrix
Path with Maximum Probability
Solution: Path with Maximum Probability
Tree Diameter
Solution: Tree Diameter
Reorder Routes to Make All Paths Lead to the City Zero
Solution: Reorder Routes to Make All Paths Lead to the City Zero

21.

Tree Depth-First Search

31 Lessons

Follow the process of exploring DFS techniques to solve various binary tree problems.
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

24.

Hash Maps

38 Lessons

Unpack the core of hash maps, designing and implementing key-value operations, and solving optimization problems.
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
Number of Wonderful Substrings
Solution: Number of Wonderful Substrings
Total Appeal of a String
Solution: Total Appeal of a String
Smallest Rectangle Enclosing Black Pixels
Solution: Smallest Rectangle Enclosing Black Pixels
Number of Distinct Islands
Solution: Number of Distinct Islands
Custom Sort String
Solution: Custom Sort String
Continuous Subarray Sum
Solution: Continuous Subarray Sum
Unique Number of Occurrences
Solution: Unique Number of Occurrences
Longest Happy Prefix
Solution: Longest Happy Prefix
Find Longest Self-Contained Substring
Solution: Find Longest Self-Contained Substring
Longest Palindrome

25.

Knowing What to Track

30 Lessons

Examine tracking techniques for data handling involving counting, palindromes, anagrams, stacks, and game design.
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
Pairs of Songs With Total Durations Divisible by 60
Solution: Pairs of Songs With Total Durations Divisible by 60
Rank Teams by Votes
Solution: Rank Teams by Votes
Minimum Number of Pushes to Type Word II
Solution: Minimum Number of Pushes to Type Word II
Task Scheduler
Solution: Task Scheduler
Count Anagrams
Solution: Count Anagrams
Divide Array Into Increasing Sequences
Solution: Divide Array Into Increasing Sequences
Ransom Note

28.

Bitwise Manipulation

30 Lessons

Focus on mastering efficient bitwise manipulation for solving diverse computational problems.
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
Count Triplets That Can Form Two Arrays of Equal XOR
Solution: Count Triplets That Can Form Two Arrays of Equal XOR
Longest Subarray With Maximum Bitwise AND
Solution: Longest Subarray With Maximum Bitwise AND
Minimum One Bit Operations to Make Integers Zero
Solution: Minimum One Bit Operations to Make Integers Zero
Triples with Bitwise AND Equal To Zero
Solution: Triples with Bitwise AND Equal To Zero
Reverse Bits

29.

Math and Geometry

35 Lessons

Explore mathematical and geometric coding challenges, focusing on efficient problem-solving techniques.
Introduction to Math and Geometry
Check If It Is a Straight Line
Solution: Check If It Is a Straight Line
Minimum Cuts to Divide a Circle
Solution: Minimum Cuts to Divide a Circle
Rectangle Overlap
Solution: Rectangle Overlap
Minimum Time Visiting All Points
Solution: Minimum Time Visiting All Points
Reverse Integer
Solution: Reverse Integer
Valid Square
Solution: Valid Square
Rectangle Area
Solution: Rectangle Area
Minimum Area Rectangle
Solution: Minimum Area Rectangle
Maximum Area Rectangle With Point Constraints I
Solution: Maximum Area Rectangle With Point Constraints I
Convex Polygon
Solution: Convex Polygon
Queries on Number of Points Inside a Circle
Solution: Queries on Number of Points Inside a Circle
Max Points on a Line
Solution: Max Points on a Line
Maximum Number of Visible Points
Solution: Maximum Number of Visible Points
Minimize Manhattan Distances
Solution: Minimize Manhattan Distances
Self Crossing
Solution: Self Crossing
Erect the Fence
Solution: Erect the Fence
Minimum Number of Lines to Cover Points
Detonate the Maximum Bombs

30.

Challenge Yourself

40 Lessons

Test your understanding of advanced coding problems to enhance problem-solving skills independently.
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

31.

Conclusion

1 Lessons

Learn how to use essential skills to excel in coding interviews.
Where to Go from Here?
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
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Frequently Asked Questions

Is Golang good for a coding interview?

Yes, Go (Golang) is good for coding interviews. Its syntax is straightforward to understand, lacking jargon in languages like Java. By avoiding features like inheritance, Go simplifies programming, helping new developers focus on core concepts and problem-solving without getting overwhelmed by complex language features. Its built-in concurrency support and strong performance further enhance its suitability for technical interviews.

How to prepare for a coding interview in Go?

What are the common patterns in DSA (data structures and algorithms)?

How should a beginner prepare for a coding interview?

Is the course grokking the coding interview enough for FAANG interviews?

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