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.

Intermediate

943 Lessons

85h

Updated this week

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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Mock Interview

Explanations

AI-POWERED

Code Feedback

Mock Interview

This course includes

534 Playgrounds

487 Challenges

490 Quizzes

This course includes

534 Playgrounds

487 Challenges

490 Quizzes

Course Overview

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...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

What You'll Learn

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

Course Content

Getting Started

Get familiar with coding patterns to excel in solving coding interview challenges.

Course Overview

Who Should Take This Course

Two Pointers

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 Count Subarrays With Fixed Bounds Solution: Count Subarrays With Fixed Bounds Get the Maximum Score Solution: Get the Maximum Score Find the Lexicographically Largest String From Box II Solution: Find the Lexicographically Largest String From Box II Create Maximum Number Solution: Create Maximum Number Append Characters to String to Make Subsequence Solution: Append Characters to String to Make Subsequence Squares of a Sorted Array Solution: Squares of a Sorted Array Reverse String Solution: Reverse String Intersection of Two Linked Lists Solution: Intersection of Two Linked Lists Remove Element Solution: Remove Element String Compression Solution: String Compression Partition Labels Solution: Partition Labels Next Permutation Solution: Next Permutation Rotate Array Solution: Rotate Array Remove Duplicates from Sorted Array Solution: Remove Duplicates from Sorted Array

Valid Palindrome II

Fast and Slow Pointers

Work your way through fast and slow pointers to solve cycles, identify intersections, and find midpoints.

Sliding Window

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 Subarrays with K Different Integers Solution: Subarrays with K Different Integers Count Subarrays With Score Less Than K Solution: Count Subarrays With Score Less Than K Count Substrings With K-Frequency Characters II Solution: Count Substrings With K-Frequency Characters II Substring with Concatenation of All Words Solution: Substring with Concatenation of All Words Binary Subarrays With Sum Solution: Binary Subarrays With Sum

Intervals

Deepen your knowledge of merging, inserting, and intersecting intervals with optimization techniques.

Introduction to 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 Count Days Without Meetings Solution: Count Days Without Meetings Remove Covered Intervals Solution: Remove Covered Intervals Car Pooling Solution: Car Pooling Data Stream as Disjoint Intervals Solution: Data Stream as Disjoint Intervals

Meeting Rooms II

In-Place Manipulation of a Linked List

26 Lessons

Streamline linked list manipulation tasks like reversing segments, swapping nodes, and removing duplicates efficiently in-place.

Heaps

25 Lessons

Master the steps to apply heaps for dynamic data processing, maximizing profits, and efficient scheduling.

K-way merge

15 Lessons

Learn how to use K-way merge pattern for efficient merging and sorting of multiple lists.

Top K Elements

37 Lessons

Walk through efficient extraction of top-k elements in diverse real-world scenarios.

10.

Modified Binary Search

38 Lessons

Work your way through advanced binary search techniques for sorted and rotated arrays.

11.

Subsets

16 Lessons

Grasp the fundamentals of generating combinations, permutations, and balanced structures with constraints.

12.

Greedy Techniques

41 Lessons

Take a closer look at greedy algorithms, implementing solutions in various optimization problems.

13.

Backtracking

35 Lessons

Investigate backtracking techniques for optimizing problem-solving in grid-based and combinatorial challenges.

14.

Dynamic Programming

62 Lessons

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

15.

Cyclic Sort

12 Lessons

Sharpen your skills in efficiently sorting and identifying missing or corrupt integers.

16.

Topological Sort

22 Lessons

Get started with organizing tasks, compiling classes, alien dictionaries, course schedules, and matrices.

17.

Sort and Search

31 Lessons

Solve problems by organizing data through sorting and applying binary search, two-pointer, and sliding window for efficient solutions.

18.

Matrices

37 Lessons

Examine key matrix operations, transformations, and algorithmic solutions for practical problems.

19.

Stacks

30 Lessons

Grasp the fundamentals of implementing stacks for efficient sequential data management and complex problem-solving.

20.

Graphs

33 Lessons

Dig deeper into graph algorithms, covering traversal methods, shortest paths, cycles, and graph validation.

21.

Tree Depth-First Search

37 Lessons

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

22.

Tree Breadth-First Search

26 Lessons

Master the steps to efficiently perform level, zigzag, vertical, and sibling traversals in binary trees.

23.

Trie

30 Lessons

Learn how to use tries for efficient string storage, prefix search, and word suggestions.

24.

Hash Maps

46 Lessons

Unpack the core of hash maps, designing and implementing key-value operations, and solving optimization problems.

25.

Knowing What to Track

32 Lessons

Examine tracking techniques for data handling involving counting, palindromes, anagrams, stacks, and game design.

26.

Union Find

28 Lessons

Grasp the fundamentals of Union Find and its applications in various algorithmic problems.

27.

Custom Data Structures

32 Lessons

Examine various custom data structures to optimize specific requirements and enhance efficiency.

28.

Bitwise Manipulation

32 Lessons

Focus on mastering efficient bitwise manipulation for solving diverse computational problems.

29.

Math and Geometry

51 Lessons

Explore mathematical and geometric coding challenges, focusing on efficient problem-solving techniques.

30.

Challenge Yourself

40 Lessons

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

31.

Conclusion

1 Lesson

Learn how to use essential skills to excel in coding interviews.

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