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Grokking the Coding Interview Patterns in Python

The ultimate guide to coding interviews, developed by FAANG engineers. Learn patterns to tackle problems from top companies and get interview-ready in just a few hours.

4.7
1033 Lessons
17 Mock Interviews
85h
Updated 1 week ago
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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

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.

Course Author:

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 Go — with more coming soon!
ABOUT THE AUTHOR

Fahim ul Haq

Software Engineer, Distributed Storage at Meta and Microsoft, Educative (Co-founder & CEO)

Learn more about Fahim

Trusted by 2.9 million developers working at companies

I really love the course, it has been an interesting journey, I wish to learn and apply this more.

H

Hitham basheir

Learner

The platform's hands-on approach and well-structured courses have been incredibly beneficial in my learning journey. Thank you for making skill development both accessible and effective!

M

Mina b.

Kona Software Lab Ltd

I found it informative and knowledgeable in an easy manner.

A

Ashraf

Learner

The guided learning paths, especially the "Grokking the Coding Interview" series, were incredibly useful for preparing for interviews. They offered a structured way to tackle common problems and learn from well-explained solutions.

S

Sumit S

Learner

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Frequently Asked Questions

Is Python good for coding interviews?

Python is a great choice for coding interviews because it is a popular programming language with all the core data structures and algorithms. Its clean syntax allows you to write code efficiently without worrying about time constraints during the interview.

How to crack Python coding interviews?

To crack Python coding interviews, focus on practicing and mastering core data structures (like lists, dictionaries, and sets), algorithms (sorting, searching, and dynamic programming), and problem-solving patterns. You can use platforms like Educative, LeetCode, or HackerRank to practice coding problems regularly. Additionally, learn to write clean, optimized code and explain your thought process during interviews.

Which is better for Python, HackerRank, or LeetCode?

LeetCode offers diverse problems for interview prep, and HackerRank is great for learning Python basics. However, Educative stands out by combining interactive lessons to learn Python deeply and coding challenges to practice, all in one platform, making it the ideal choice for comprehensive interview preparation.

Does Google allow Python in coding interviews?

Yes, Google allows Python in coding interviews, and it’s a popular choice due to its simplicity and readability.

How many problems are in grokking the coding interview?

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:

  • Cyclic sort: It sorts elements in a range by placing them correctly.
  • Two pointers: It moves pointers from both ends to solve pair or rearrangement problems.
  • Sliding window: It adjusts a window over data to solve subarray or substring problems.
  • Merge intervals: It combines overlapping intervals into single ranges.
  • Fast and slow pointers: It detects cycles or finds elements using two different speed pointers.

Practicing these ensures comprehensive preparation for coding interviews at top tech companies like FAANG.