Name: Grokking the Coding Interview Patterns in JavaScript
Rating: 4.7 (3 reviews)

Grokking the Coding Interview Patterns in JavaScript

Coding interview coming up? Try this battle-tested prep plan created by FAANG devs. Master essential data structures & algorithms in JavaScript, and learn patterns to get interview-ready faster.

Intermediate

439 Lessons

85h

Certificate of Completion

Coding interview coming up? Try this battle-tested prep plan created by FAANG devs. Master essential data structures & algorithms in JavaScript, and learn patterns to get interview-ready faster.

AI-POWERED

Code Feedback

Mock Interview

Explanations

AI-POWERED

Code Feedback

Mock Interview

This course includes

294 Playgrounds

234 Challenges

235 Quizzes

This course includes

294 Playgrounds

234 Challenges

235 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

TAKEAWAY SKILLS

Data Structures

Programming Language

Python

Prepare For Interview

Coding Interview Patterns

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

In this chapter, you’ll get a high-level introduction to the course, including structure, objectives, and strategic interview approaches.

Course Overview

Who Should Take This Course

Two Pointers

In this chapter, you will learn how to solve problems using Two Pointers, like checking for palindromes, removing nodes from lists, and reversing strings.

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

Valid Palindrome II

Fast and Slow Pointers

This chapter focuses on solving problems using Fast and Slow Pointers, such as detecting cycles, finding middle elements, and more in linked lists.

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

Sliding Window

Learn the Sliding Window pattern to solve problems by adjusting a window over data to handle maximums, minimums, and substrings.

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

Best Time to Buy and Sell Stock

Merge Intervals

In this chapter, you’ll learn the Merge Intervals pattern, solving problems by merging overlapping intervals and managing continuous data segments.

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

In-Place Manipulation of a Linked List

14 Lessons

Learn techniques for in-place manipulation of linked lists, including reversing nodes and restructuring groups.

Two Heaps

11 Lessons

In this chapter, you’ll cover the Two Heaps pattern to maintain a sorted list of elements and solve problems like finding medians and managing dynamic datasets.

K-way merge

11 Lessons

In this chapter, you’ll learn K-way Merge techniques for efficiently combining multiple sorted arrays or lists into a single sorted sequence.

Top K Elements

11 Lessons

This chapter explores heap-based techniques for efficiently finding the k most/least frequent or k largest/smallest elements in a dataset.

10.

Modified Binary Search

18 Lessons

In this chapter, you’ll explore Modified Binary Search, solving problems involving sorted arrays and ranges by efficiently dividing the search space.

11.

Subsets

10 Lessons

In this chapter, you’ll cover the Subsets pattern, solving problems that involve generating all possible subsets or combinations of a given set.

12.

Greedy Techniques

14 Lessons

In this chapter, you’ll explore Greedy Techniques for solving optimization problems, making locally optimal choices to achieve the best overall solution.

13.

Backtracking

15 Lessons

In this chapter, you’ll discover how to solve problems using Backtracking, like N-Queens, Word Search, and Sudoku, by exploring all possible paths.

14.

Dynamic Programming

32 Lessons

This chapter explores how to solve problems using Dynamic Programming, focusing on solving complex problems by breaking them into manageable subproblems.

15.

Cyclic Sort

8 Lessons

This chapter focuses on Cyclic Sort, teaching methods for sorting integers within a range to solve problems such as missing numbers and duplicates effectively.

16.

Topological Sort

12 Lessons

In this chapter, you’ll explore Topological Sort to solve problems involving directed graphs by linearly ordering vertices based on their dependencies.

17.

Matrices

11 Lessons

This chapter focuses on matrix operations, including traversal, setting zeros, rotating images, and other grid-based transformations.

18.

Stacks

14 Lessons

In this chapter, you will explore Stacks, a LIFO data structure, to solve problems like balancing parentheses, evaluating expressions, and more efficiently.

19.

Graphs

13 Lessons

In this chapter, you’ll learn how to solve various problems using Graphs, including traversal, shortest path finding, and connectivity in network structures.

20.

Tree Depth-First Search

29 Lessons

In this chapter, you’ll discover how to solve problems using Tree Depth-first Search (DFS), including binary tree traversals, pathfinding, and subtree analysis.

21.

Tree Breadth-First Search

14 Lessons

In this chapter, you’ll cover Tree Breadth-first Search (BFS) techniques for level order traversal, shortest path finding, and node connectivity.

22.

Trie

16 Lessons

Learn about Tries to solve problems involving string manipulation, prefix searches, and auto-completion efficiently

23.

Hash Maps

18 Lessons

This chapter covers using Hash Maps with key-value pairs for efficient frequency counts, lookups, and managing duplicates.

24.

Knowing What to Track

18 Lessons

In this chapter, you'll learn techniques for Knowing What to Track when solving problems by monitoring data like counts, indices, and states.

25.

Union Find

18 Lessons

The chapter explores the Union-Find data structure and its applications, covering various problems and optimized solutions for efficient data handling.

26.

Custom Data Structures

18 Lessons

This chapter explores how to solve specialized problems by designing Custom Data Structures and optimizing performance for unique use cases.

27.

Bitwise Manipulation

16 Lessons

Learn how to solve problems using Bitwise Manipulation by applying bit operations for tasks like binary conversions, masking, and efficient arithmetic.

28.

Challenge Yourself

40 Lessons

This chapter offers challenging problems to reinforce and apply your knowledge of different coding patterns.

29.

Conclusion

1 Lesson

The chapter emphasizes the importance of continued learning, community support, and hands-on practice for successful coding interview preparation.

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