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

763 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

445 Playgrounds

397 Challenges

398 Quizzes

This course includes

445 Playgrounds

397 Challenges

398 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

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

Course Content

Getting Started

Get familiar with coding design patterns to enhance your problem-solving skills for interviews.

Course Overview

Who Should Take This Course

Two Pointers

Get started with two-pointers to solve linear data structure problems efficiently.

Two Pointers

Fast and Slow Pointers

Master the steps to use fast and slow pointers for cycle detection and mid-point identification.

Fast and Slow Pointers

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 Fruit Into Baskets Solution: Fruit Into Baskets Contains Duplicate II Solution: Contains Duplicate II Frequency of the Most Frequent Element Solution: Frequency of the Most Frequent Element Subarrays with K Different Integers Solution: Subarrays with K Different Integers Count Subarrays With Score Less Than K Solution: Count Subarrays With Score Less Than K

Sliding Window

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 Count Days Without Meetings Solution: Count Days Without Meetings Remove Covered Intervals Solution: Remove Covered Intervals

Meeting Rooms II

In-Place Manipulation of a Linked List

24 Lessons

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

Heaps

23 Lessons

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

Heaps

K-way merge

15 Lessons

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

Top K Elements

33 Lessons

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

10.

Modified Binary Search

28 Lessons

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

10.

Modified Binary Search

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

27 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.

14.

Dynamic Programming

15.

Cyclic Sort

12 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.

16.

Topological Sort

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

31 Lessons

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

19.

Stacks

26 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.

20.

Graphs

21.

Tree Depth-First Search

31 Lessons

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

22.

Tree Breadth-First Search

20 Lessons

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

22.

Tree Breadth First Search

23.

Trie

22 Lessons

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

24.

Hash Maps

36 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

22 Lessons

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

26.

Union Find

27.

Custom Data Structures

26 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

35 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 Lesson

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

31.

Coding Patterns

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