Home>
Courses>

Grokking the Coding Interview Patterns in Python

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.

Intermediate

533 Lessons

85h

Certificate of Completion

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.

AI-POWERED

Code Feedback
Mock Interview
Explanations

AI-POWERED

Code Feedback
Mock Interview

This course includes

341 Playgrounds
281 Challenges
282 Quizzes

This course includes

341 Playgrounds
281 Challenges
282 Quizzes
Course Overview
What You'll Learn
Course Content

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

Python

Programming Language

Coding Interview Patterns

Data Structures

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

Show more

Course Content

1.

Getting Started

Get familiar with coding design patterns to enhance your problem-solving skills for interviews.
Course Overview
Who Should Take This Course
2.

Two Pointers

Get started with two-pointers to solve linear data structure problems efficiently.
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
Valid Palindrome II
3.

Fast and Slow Pointers

Master the steps to use fast and slow pointers for cycle detection and mid-point identification.
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
Maximum Twin Sum of a Linked List
Solution: Maximum Twin Sum of a Linked List
Split a Circular Linked List
Solution: Split a Circular Linked List
4.

Sliding Window

Break down the sliding window technique to solve computational problems with optimized efficiency.
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
Best Time to Buy and Sell Stock
5.

Merge Intervals

Solve problems in merging intervals, inserting and finding intersections of intervals, scheduler tasks, and determining employee free time.
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
6.

In-Place Manipulation of a Linked List

16 Lessons

Tackle in-place linked list manipulations for efficient and memory-optimized operations.
7.

Two Heaps

15 Lessons

Practice using two heaps to solve dynamic data processing and optimization problems efficiently.
8.

K-way merge

11 Lessons

Learn how to use k-way merge for efficient data merging and finding k-th small elements.
9.

Top K Elements

17 Lessons

Walk through the top k elements pattern and learn efficient selection using heaps.
10.

Modified Binary Search

18 Lessons

Break apart modified binary search adaptations and solutions for diverse search problems.
11.

Subsets

10 Lessons

Grasp the fundamentals of generating subsets, permutations, and combinations in Python.
12.

Greedy Techniques

20 Lessons

Dig into optimization problems with greedy algorithms through practical scenarios and solutions.
13.

Backtracking

17 Lessons

Explore backtracking algorithm for solving complex problems like N-Queens, word search, binary tree paths, and Sudoku.
14.

Dynamic Programming

32 Lessons

Build on dynamic programming concepts to efficiently solve complex optimization problems.
15.

Cyclic Sort

8 Lessons

Step through cyclic sort concepts to efficiently handle various missing and corrupt number scenarios.
16.

Topological Sort

16 Lessons

Unpack the core of topological sort, focusing on ordering dependencies and resolving compilation sequences efficiently.
17.

Matrices

17 Lessons

Go hands-on with matrix operations, transformations, and efficient traversal techniques in coding.
18.

Stacks

18 Lessons

Apply your skills to use stacks for various tasks, including calculators, string manipulation, and queuing.
19.

Graphs

17 Lessons

Deepen your knowledge of graph theory, algorithms, practical solutions, and real-world applications.
20.

Tree Depth-First Search

31 Lessons

Follow the process of exploring tree structures and implementing various binary tree problems.
21.

Tree Breadth-First Search

14 Lessons

Piece together the parts of the Tree BFS traversal, focusing on various traversal methods.
22.

Trie

18 Lessons

Step through efficient trie implementations to optimize search suggestions, word replacements, and common prefix finding.
23.

Hash Maps

32 Lessons

Discover the logic behind implementing efficient hash maps and their applications in problem-solving.
24.

Knowing What to Track

24 Lessons

Master the steps to efficiently track data, solve permutations, anagrams, and game design problems.
25.

Union Find

22 Lessons

Enhance your skills in Union-Find to address diverse graph and connectivity problems.
26.

Custom Data Structures

24 Lessons

Dig into creating and implementing custom data structures for solving specialized problems efficiently.
27.

Bitwise Manipulation

22 Lessons

Explore bitwise operations for problem-solving and algorithm optimization in Python.
28.

Challenge Yourself

40 Lessons

Test your understanding of various coding challenges focusing on algorithm efficiency.
29.

Conclusion

1 Lesson

Learn how to use coding interview skills and engage in continuous learning.

Practice and apply your skills

Trusted by 1.4 million developers working at companies

Hitham basheir

Learner

Mina b.

Kona Software Lab Ltd

Ashraf

Learner

Sumit S

Learner

Hitham basheir

Learner

Mina b.

Kona Software Lab Ltd

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Instant Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI-Powered Mock Interviews

Adaptive Learning

Explain with AI

AI Code Mentor

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?

Which is better for Python, HackerRank, or LeetCode?

Does Google allow Python in coding interviews?

How many problems are in grokking the coding interview?