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Grokking the Coding Interview Patterns in JavaScript - AI-Powered Course 
JavaScript
4.3
Intermediate
85h
Updated this week
Grokking the Coding Interview Patterns in JavaScript
The ultimate guide to coding interviews in JavaScript. Developed by FAANG engineers. Learn essential patterns, practice with real-world questions, and get interview-ready in just a few hours.
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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 Python, C++, Java, and Go — 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
TAKEAWAY SKILLS
Data Structures
Programming Language
Python
Prepare for Interview
Coding Interview Patterns
Content
835 Lessons434 Quizzes433 Challenges
1.
Getting Started
2 Lessons
Learn how to use coding patterns for effective interview problem-solving with 215 challenges.
2.
Two Pointers
38 Lessons
Get started with Two Pointers for efficient array and string manipulation techniques.
Introduction to Two PointersValid PalindromeSolution: Valid Palindrome3SumSolution: 3SumRemove Nth Node from End of ListSolution: Remove Nth Node from End of ListSort ColorsSolution: Sort ColorsReverse Words in a StringSolution: Reverse Words in a StringValid Word AbbreviationSolution: Valid Word AbbreviationStrobogrammatic NumberSolution: Strobogrammatic NumberMinimum Number of Moves to Make PalindromeSolution: Minimum Number of Moves to Make PalindromeNext Palindrome Using Same DigitsSolution: Next Palindrome Using Same DigitsLowest Common Ancestor of a Binary Tree IIISolution: Lowest Common Ancestor of a Binary Tree IIICount Pairs Whose Sum is Less than TargetSolution: Count Pairs Whose Sum is Less than TargetCount Subarrays With Fixed BoundsSolution: Count Subarrays With Fixed BoundsGet the Maximum ScoreSolution: Get the Maximum ScoreFind the Lexicographically Largest String From Box IISolution: Find the Lexicographically Largest String From Box IICreate Maximum NumberSolution: Create Maximum NumberAppend Characters to String to Make SubsequenceSolution: Append Characters to String to Make SubsequenceSquares of a Sorted ArraySolution: Squares of a Sorted ArrayReverse StringSolution: Reverse StringValid Palindrome II
3.
Fast and Slow Pointers
21 Lessons
Examine the fast and slow pointers technique for cycle detection, middle node identification, and efficient data traversal.
4.
Sliding Window
31 Lessons
Grasp the fundamentals of the sliding window technique for efficient array and string manipulation.
5.
Intervals
18 Lessons
Take a closer look at merging, inserting, and intersecting intervals for optimal scheduling.
6.
In-Place Manipulation of a Linked List
24 Lessons
Tackle in-place linked list manipulation for scenarios like reversing, swapping nodes, and removing duplicates using space-efficient techniques.
7.
Heaps
25 Lessons
Build on using heaps to optimize dynamic data processing, median calculations, and task scheduling.
8.
K-way merge
15 Lessons
Learn how to use the K-way merge for efficient sorting and finding specific elements.
9.
Top K Elements
37 Lessons
Get started with techniques to efficiently identify the top K elements in unsorted collections.
10.
Modified Binary Search
32 Lessons
Work your way through modified binary search techniques, including real-world applications and various problem-solving strategies.
11.
Subsets
14 Lessons
Grasp the fundamentals of generating subsets, permutations, and letter combinations, using efficient algorithms.
12.
Greedy Techniques
31 Lessons
Take a closer look at greedy algorithms for optimal solutions in various coding challenges.
13.
Backtracking
33 Lessons
Follow the process of utilizing backtracking to solve various algorithmic challenges efficiently.
14.
Dynamic Programming
36 Lessons
Master dynamic programming by exploring optimization techniques to solve various algorithmic problems efficiently.
15.
Cyclic Sort
12 Lessons
Learn how to use cyclic sort for efficient sorting, missing numbers, and corrupt pairs.
16.
Topological Sort
18 Lessons
Walk through topological sorting for organizing tasks, class compilation, alien dictionary challenges, course schedules, and matrix construction.
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
35 Lessons
Examine key matrix operations and solutions for various matrix-related coding problems.
19.
Stacks
28 Lessons
Grasp the fundamentals of stack data structures and their practical applications in coding.
20.
Graphs
31 Lessons
Deepen your knowledge of graph fundamentals, traversal techniques, and key graph algorithms.
21.
Tree Depth-First Search
35 Lessons
Simplify complex topics like tree depth-first search and solving binary tree problems efficiently.
22.
Tree Breadth-First Search
24 Lessons
Master the steps to efficiently traverse binary trees with BFS for various problem-solving applications.
23.
Trie
28 Lessons
Get familiar with the trie data structure for efficient string storage and prefix matching.
24.
Hash Maps
38 Lessons
Discover the logic behind hash map creation, key operations, and diverse applications.
25.
Knowing What to Track
30 Lessons
Explore effectively tracking elements in data sets for solving common coding problems.
26.
Union Find
28 Lessons
Grasp the fundamentals of Union Find, solving graph and connectivity problems efficiently.
27.
Custom Data Structures
32 Lessons
Deepen your knowledge of creating custom data structures for specialized problem-solving in JavaScript.
28.
Bitwise Manipulation
30 Lessons
Implement bitwise manipulation techniques for solving problems efficiently, with applications in cryptography, compression, and data encoding.
29.
Math and Geometry
37 Lessons
Explore mathematical concepts and geometric properties to solve various coding challenges.
30.
Challenge Yourself
40 Lessons
Challenge yourself with coding problems, improving problem-solving skills with practice and application.
31.
Conclusion
1 Lessons
Get familiar with further resources, hands-on practice, and the supportive community for interviews.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Developed by MAANG Engineers
Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.
Trusted by 2.8 million developers working at companies
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Related Courses and Skill Paths
Free Resources
Frequently Asked Questions
Is JavaScript allowed in coding interviews?
Yes, JavaScript is commonly allowed in coding interviews, especially for web development roles. It supports all essential data structures and algorithms, making it suitable for solving various problems. Its straightforward syntax helps you write clean code efficiently, which is beneficial during time-constrained interviews.
How to practice a JavaScript coding interview?
To practice JavaScript coding interviews, focus on solving coding problems on platforms like Educative, LeetCode, and HackerRank, which offer various challenges. Study common data structures and algorithms and practice writing clean, efficient code. Review JavaScript-specific concepts like closures, promises, and async/await to be well-prepared for technical questions.
Is cracking the coding interview enough for FAANG?
While cracking the coding Interview has a significant impact, it’s often not enough to pass the FAANG interviews. You must do additional study and practice study system design and behavioral questions on coding platforms like Educative.
Does GitHub have resources for grokking coding interview patterns in JavaScript?
Yes, GitHub has resources for grokking coding interview patterns in JavaScript. Educative has its popular listings on GitHub, which list various coding problems and patterns, allowing you to pick and choose the ones that best fit your needs. This helps you focus on specific areas for improvement and tailor your preparation to the problems you’re most likely to encounter in interviews.
How many problems are in grokking the coding interview in JavaScript?
Our Grokking the Coding Interview course at Educative currently offers 228 LeetCode coding problems categorized under key coding patterns, and we’re continuously updating this number. Some of the patterns include:
- Topological sort: It orders tasks based on dependencies using directed graphs.
- Backtracking: It explores all possible solutions by trying and undoing choices.
- Dynamic programming: It solves problems by breaking them into overlapping subproblems and storing results.
- Greedy algorithm: It makes the locally optimal choice to find a global solution at each step.
- Tree Depth-first search (DFS): It explores as far as possible along each branch before backtracking.
This ensures comprehensive preparation for coding interviews at top tech companies like FAANG.
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