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.
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Grokking the Coding Interview Patterns in Go
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.
5.0
1033 Lessons
17 Mock Interviews
85h
Updated yesterday
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Select your Language
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- 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
Why choose this course?
Learn 28 Non-negotiable Coding Patterns
Begin your journey with core coding patterns such as Two Pointers, Binary Search, and Linked List manipulation. Each problem comes as a paired challenge and solution: first, implement your own approach, then study a step-by-step optimal sol
Master Advanced Algorithms and Data Structures
Level up with complex topics such as Dynamic Programming, Graphs, Tries, and Union Find. These advanced patterns often appear in the toughest interviews and will prepare you to approach difficult questions with confidence and clarity.
Mock Interviews for Every Coding Pattern
At the end of each chapter, take an AI-driven mock interview. Practice under real conditions and strengthen your ability to explain solutions clearly.
Put Your Skills to the Test
Wrap up your preparation in the Challenge Yourself section, where problems are presented without pattern labels. This sharpens your ability to recognize the right approach on your own, just like in a real interview.
Learning Roadmap
1.
Two Pointers
Get started with two-pointers to solve linear data structure problems efficiently.
Introduction to Two Pointers
Valid Palindrome
Easy
3Sum
Medium
Remove nth Node from End of List
Medium
Sort Colors
Medium
Reverse Words in a String
Medium
Valid Word Abbreviation
Easy
Valid Palindrome II
Easy
Lowest Common Ancestor of a Binary Tree III
Medium
Strobogrammatic Number
Easy
Minimum Number of Moves to Make Palindrome
Hard
Next Palindrome Using Same Digits
Hard
Count Subarrays With Fixed Bounds
Hard
Find the Lexicographically Largest String From Box II
Hard
Get the Maximum Score
Hard
Create Maximum Number
Hard
Append Characters to String to Make Subsequence
Medium
Squares of a Sorted Array
Easy
Reverse String
Easy
Intersection of Two Linked Lists
Easy
Partition Labels
Medium
Remove Element
Easy
String Compression
Medium
Rotate Array
Medium
Next Permutation
Medium
Remove Duplicates from Sorted Array
Easy
Reverse Vowels of a String
Medium
Is Subsequence
Medium
2.
Fast and Slow Pointers
Master the steps to use fast and slow pointers for cycle detection and mid-point identification.
Introduction to Fast and Slow Pointers
Happy Number
Easy
Linked List Cycle
Easy
Middle of the Linked List
Easy
Circular Array Loop
Medium
Find The Duplicate Number
Medium
Palindrome Linked List
Easy
Linked List Cycle III
Medium
Linked List Cycle IV
Medium
Maximum Twin Sum of a Linked List
Medium
Split a Circular Linked List
Medium
3.
Sliding Window
Break down the sliding window technique to solve computational problems with optimized efficiency.
4.
Intervals
Solve problems in merging intervals, inserting and finding intersections of intervals, scheduler tasks, and determining employee free time.
5.
In-Place Manipulation of a Linked List
Tackle in-place linked list manipulations for efficient and memory-optimized operations.
6.
Two Heaps
Master the steps to optimize dynamic data processing and decision-making using heaps.
7.
K-way Merge
Learn how to use k-way merge for efficient data merging and finding k-th small elements.
8.
Top K Elements
Walk through the top k elements pattern and learn efficient selection using heaps.
9.
Modified Binary Search
Break apart modified binary search adaptations and solutions for diverse search problems.
10.
Subsets
Grasp the fundamentals of generating subsets, permutations, and combinations.
11.
Greedy Techniques
Dig into optimization problems with greedy algorithms through practical scenarios and solutions.
12.
Backtracking
Explore backtracking algorithm for solving complex problems like N-Queens, word search, binary tree paths, and Sudoku.
13.
Dynamic Programming
Build on dynamic programming concepts to efficiently solve complex optimization problems.
14.
Cyclic Sort
Step through cyclic sort concepts to efficiently handle various missing and corrupt number scenarios.
15.
Topological Sort
Unpack the core of topological sort, focusing on ordering dependencies and resolving compilation sequences efficiently.
16.
Sort and Search
Solve problems by organizing data through sorting and applying binary search, two-pointer, and sliding window for efficient solutions.
17.
Matrices
Go hands-on with matrix operations, transformations, and efficient traversal techniques in coding.
18.
Stacks
Apply your skills to use stacks for various tasks, including calculators, string manipulation, and queuing.
19.
Graphs
Deepen your knowledge of graph theory, algorithms, practical solutions, and real-world applications.
20.
Tree Depth-First Search
Follow the process of exploring tree structures and implementing various binary tree problems.
21.
Tree Breadth-First Search
Piece together the parts of the Tree BFS traversal, focusing on various traversal methods.
22.
Trie
Step through efficient trie implementations to optimize search suggestions, word replacements, and common prefix finding.
23.
Hash Maps
Discover the logic behind implementing efficient hash maps and their applications in problem-solving.
24.
Knowing What to Track
Master the steps to efficiently track data, solve permutations, anagrams, and game design problems.
25.
Union Find
Enhance your skills in Union-Find to address diverse graph and connectivity problems.
26.
Custom Data Structures
Dig into creating and implementing custom data structures for solving specialized problems efficiently.
27.
Bitwise Manipulation
Explore bitwise operations for problem-solving and algorithm optimization.
28.
Math and Geometry
Explore math and geometry for problem-solving.
29.
Challenge Yourself
Test your understanding of various coding challenges focusing on algorithm efficiency.
Developed by MAANG Engineers
ABOUT THIS COURSE
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!
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Evan Dunbar
ML Engineer
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Software Developer
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Front-end Developer
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Vinay Krishnaiah
Software Developer
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Frequently Asked Questions
Is Golang good for a coding interview?
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?
