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Grokking the Coding Interview Patterns in Python - AI-Powered Course 
Python
4.6
Intermediate
85h
Updated this week
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.
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Overview
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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 JavaScript, 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
Python
Programming Language
Coding Interview Patterns
Data Structures
Content
835 Lessons434 Quizzes433 Challenges
1.
Getting Started
2 Lessons
Get familiar with coding design patterns to enhance your problem-solving skills for interviews.
2.
Two Pointers
38 Lessons
Get started with two-pointers to solve linear data structure problems efficiently.
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
Master the steps to use fast and slow pointers for cycle detection and mid-point identification.
4.
Sliding Window
31 Lessons
Break down the sliding window technique to solve computational problems with optimized efficiency.
5.
Intervals
18 Lessons
Solve problems in merging intervals, inserting and finding intersections of intervals, scheduler tasks, and determining employee free time.
6.
In-Place Manipulation of a Linked List
24 Lessons
Tackle in-place linked list manipulations for efficient and memory-optimized operations.
7.
Heaps
25 Lessons
Practice using heaps to solve dynamic data processing and optimization problems efficiently.
8.
K-way merge
15 Lessons
Learn how to use k-way merge for efficient data merging and finding k-th small elements.
9.
Top K Elements
37 Lessons
Walk through the top k elements pattern and learn efficient selection using heaps.
10.
Modified Binary Search
32 Lessons
Break apart modified binary search adaptations and solutions for diverse search problems.
11.
Subsets
14 Lessons
Grasp the fundamentals of generating subsets, permutations, and combinations in Python.
12.
Greedy Techniques
31 Lessons
Dig into optimization problems with greedy algorithms through practical scenarios and solutions.
13.
Backtracking
33 Lessons
Explore backtracking algorithm for solving complex problems like N-Queens, word search, binary tree paths, and Sudoku.
14.
Dynamic Programming
36 Lessons
Build on dynamic programming concepts to efficiently solve complex optimization problems.
15.
Cyclic Sort
12 Lessons
Step through cyclic sort concepts to efficiently handle various missing and corrupt number scenarios.
16.
Topological Sort
18 Lessons
Unpack the core of topological sort, focusing on ordering dependencies and resolving compilation sequences efficiently.
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
Go hands-on with matrix operations, transformations, and efficient traversal techniques in coding.
19.
Stacks
28 Lessons
Apply your skills to use stacks for various tasks, including calculators, string manipulation, and queuing.
20.
Graphs
31 Lessons
Deepen your knowledge of graph theory, algorithms, practical solutions, and real-world applications.
21.
Tree Depth-First Search
35 Lessons
Follow the process of exploring tree structures and implementing various binary tree problems.
22.
Tree Breadth-First Search
24 Lessons
Piece together the parts of the Tree BFS traversal, focusing on various traversal methods.
23.
Trie
28 Lessons
Step through efficient trie implementations to optimize search suggestions, word replacements, and common prefix finding.
24.
Hash Maps
38 Lessons
Discover the logic behind implementing efficient hash maps and their applications in problem-solving.
25.
Knowing What to Track
30 Lessons
Master the steps to efficiently track data, solve permutations, anagrams, and game design problems.
26.
Union Find
28 Lessons
Enhance your skills in Union-Find to address diverse graph and connectivity problems.
27.
Custom Data Structures
32 Lessons
Dig into creating and implementing custom data structures for solving specialized problems efficiently.
28.
Bitwise Manipulation
30 Lessons
Explore bitwise operations for problem-solving and algorithm optimization in Python.
29.
Math and Geometry
37 Lessons
Explore mathematical and geometric coding challenges, focusing on efficient problem-solving techniques.
30.
Challenge Yourself
40 Lessons
Test your understanding of various coding challenges focusing on algorithm efficiency.
31.
Conclusion
1 Lessons
Learn how to use coding interview skills and engage in continuous learning.
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
"I really love the course, it has been an interesting journey, I wish to learn and apply this more."
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!"
Mina b.
Kona Software Lab Ltd
"I found it informative and knowledgeable in an easy manner."
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."
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.
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