Efficiently prepare for coding interviews in Python with strategies from FAANG engineers. Avoid the LeetCode grind and simplify your Python interview prep with real-world questions from top companies.

Intermediate

427 Lessons

85h

Certificate of Completion

Efficiently prepare for coding interviews in Python with strategies from FAANG engineers. Avoid the LeetCode grind and simplify your Python interview prep with real-world questions from top companies.

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This course includes

288 Playgrounds

228 Challenges

229 Quizzes

This course includes

288 Playgrounds

228 Challenges

229 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...

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

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Course Content

1.

Getting Started

In this chapter, you’ll cover the course introduction, target audience, and course objectives.

2.

Two Pointers

This chapter focuses on the Two Pointers technique, solving palindrome validation, array summation, and reordering problems.

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 AbbreviationValid Palindrome II

3.

Fast and Slow Pointers

In this chapter, you’ll explore Fast and Slow Pointers for detecting cycles and finding midpoints in linked lists.

Introduction to Fast and Slow PointersHappy NumberSolution: Happy NumberLinked List CycleSolution: Linked List CycleMiddle of the Linked ListSolution: Middle of the Linked ListCircular Array LoopSolution: Circular Array LoopFind the Duplicate NumberSolution: Find the Duplicate NumberPalindrome Linked ListSolution: Palindrome Linked List

4.

Sliding Window

This chapter covers the Sliding Window technique with problems on substring search, window maximums, and repeating characters.

Introduction to Sliding WindowRepeated DNA SequencesSolution: Repeated DNA SequencesSliding Window MaximumSolution: Sliding Window MaximumMinimum Window SubsequenceSolution: Minimum Window SubsequenceLongest Repeating Character ReplacementSolution: Longest Repeating Character ReplacementMinimum Window SubstringSolution: Minimum Window SubstringLongest Substring without Repeating CharactersSolution: Longest Substring without Repeating CharactersMinimum Size Subarray SumSolution: Minimum Size Subarray SumBest Time to Buy and Sell Stock

5.

Merge Intervals

In this chapter, you’ll learn about merging and inserting intervals, scheduling tasks, and finding intersections.

Introduction to Merge IntervalsMerge IntervalsSolution: Merge IntervalsInsert IntervalSolution: Insert IntervalInterval List IntersectionsSolution: Interval List IntersectionsEmployee Free TimeSolution: Employee Free TimeTask SchedulerSolution: Task SchedulerMeeting Rooms II

6.

In-Place Manipulation of a Linked List

14 Lessons

This chapter focuses on reversing and reordering linked lists, swapping nodes, and group-based manipulations.

7.

Two Heaps

11 Lessons

In this chapter, you'll learn about the Two Heaps technique for problems involving median maintenance, sliding window medians, and task scheduling.

8.

K-way merge

11 Lessons

This chapter covers K-way merging for sorted arrays, smallest elements in lists, and merging multiple lists.

9.

Top K Elements

11 Lessons

In this chapter, you’ll solve problems related to finding the top K elements, including kth largest element and k closest points.

10.

Modified Binary Search

16 Lessons

This chapter focuses on Modified Binary Search, tackling search problems in rotated arrays, finding closest elements, and identifying unique values.

11.

Subsets

10 Lessons

In this chapter, you'll explore subsets and permutations, generating combinations, and creating valid parentheses.

12.

Greedy Techniques

14 Lessons

In this chapter, you’ll learn greedy methods for solving problems like optimal jumps, resource allocation, and scheduling tasks.

13.

Backtracking

15 Lessons

This chapter explores backtracking, demonstrating its application in solving problems like N-Queens, Word Search, and Sudoku, among others.

14.

Dynamic Programming

32 Lessons

In this chapter, you'll learn Dynamic Programming with problems on knapsack, coin change, sequence analysis, and matrix paths.

15.

Cyclic Sort

8 Lessons

This chapter focuses on Cyclic Sort, solving problems related to missing numbers, corrupt pairs, and positive integers.

16.

Topological Sort

12 Lessons

In this chapter, you’ll explore Topological Sort for task ordering, course scheduling, and alien dictionaries.

17.

Matrices

9 Lessons

This chapter covers matrix problems like image rotation, spiral matrix, and path finding.

18.

Stacks

14 Lessons

In this chapter, you'll learn stack-based solutions for expression evaluation, duplicate removal, and valid parentheses.

19.

Graphs

13 Lessons

This chapter explores various graph concepts, algorithms, and real-world applications, including network delays, cycle detection, and graph cloning techniques.

20.

Tree Depth-First Search

29 Lessons

This chapter explores depth-first search techniques in trees, encompassing transformations, properties, and optimizations, alongside various related algorithms.

21.

Tree Breadth-First Search

14 Lessons

This chapter explores various breadth-first search techniques in trees, covering traversal methods, connecting siblings, and handling transformations.

22.

Trie

14 Lessons

This chapter explores trie structures, highlighting their capabilities in string manipulation, retrieval, and search optimization for various applications.

23.

Hash Maps

16 Lessons

In this chapter, you’ll learn about Hash Maps for frequency counting, efficient lookups, and finding duplicates.

24.

Knowing What to Track

18 Lessons

This chapter focuses on tracking occurrences of elements in data structures, emphasizing applications in permutations, anagram detection, game design, and more.

25.

Union Find

18 Lessons

In this chapter, you'll learn Union Find techniques for solving connectivity issues, island counting, and merging accounts.

26.

Custom Data Structures

16 Lessons

This chapter introduces custom data structures, tackling advanced caching, snapshot arrays, and key-value stores.

27.

Bitwise Manipulation

14 Lessons

In this chapter, you’ll explore Bitwise Manipulation for number complements, image flipping, and binary transformations.

28.

Challenge Yourself

40 Lessons

This chapter presents various coding challenges aimed at enhancing problem-solving skills through independent strategy development across diverse topics.

29.

Conclusion

1 Lesson

This chapter concludes the course, providing guidance on next steps and further learning paths.

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