HomeCoursesAlgorithms for Coding Interviews in Python

Intermediate

15h

Updated 2 months ago

Algorithms for Coding Interviews in Python

Your ultimate guide to algorithms for coding interviews. Master several must-know algorithms, and test your skills with real-world problems from top companies.

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Overview

Content

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With algorithms being one of the most common themes in coding interviews, having a firm grip on them can be the difference between being hired and not. After completing this comprehensive course, you'll have an in-depth understanding of different algorithm types in Python and be equipped with a simple process for approaching complexity analysis. As you progress, you’ll be exposed to the most important algorithms you'll likely encounter in an interview. You'll work your way through over 50 interactive coding challenges and review detailed solutions for each problem. You’ll walk away with the ability to build-up to the optimal solution for addressing those tough coding interview questions head-on.

With algorithms being one of the most common themes in coding interviews, having a firm grip on them can be the difference betwe...Show More

Content

132 Lessons17 Quizzes42 Challenges

Introduction

2 Lessons

Who This Course Is For

Learning Outcomes

Algorithmic Paradigms

4 Lessons

Asymptotic Analysis

22 Lessons

Comparing Algorithms

Example: Measuring Time Complexity - Single loop

Example: Measuring Time Complexity - Nested Loop

Introduction to Asymptotic Analysis and Big O

Other Common Asymptotic Notations and Why Big O Trumps Them

Useful Formulas

Common Complexity Scenarios

Challenge: Big O of Nested Loop With Addition

Solution: Big O of Nested Loop With Addition

Challenge: Big O of Nested Loop With Subtraction

Solution: Big O of Nested Loop With Subtraction

Challenge: Big O of Nested Loop With Multiplication

Solution: Big O of Nested Loop With Multiplication

Challenge: Nested Loop With Multiplication (Basic)

Solution: Nested Loop With Multiplication (Basic)

Challenge: Nested Loop With Multiplication (Intermediate)

Solution: Nested Loop With Multiplication (Intermediate)

Challenge: Nested Loop With Multiplication (Advanced)

Solution: Nested Loop With Multiplication (Advanced)

Challenge: Nested Loop With Multiplication (Pro)

Solution: Nested Loop With Multiplication (Pro)

Complexity Quiz: Test Your Understanding of Complexity

Sorting & Searching

24 Lessons

Selection Sort, Bubble Sort, and Insertion Sort

Merge Sort

Quick Sort

Overview of Sorting Algorithms

Searching Algorithms

Challenge: Find Two Numbers That Add Up to "n"

Solution: Find Two Numbers That Add Up to "n"

Challenge: Search in a Rotated List

Solution: Search in a Rotated List

Challenge: Group Anagrams

Solution: Group Anagrams

Challenge: Arrange a Binary List

Solution: Arrange a Binary List

Challenge: Find the Maximum Product of Two Integers in a List

Solution: Find the Maximum Product of Two Integers in a List

Challenge: Find Duplicates in a List With No Repetition

Solution: Find Duplicates in a List With No Repetition

Challenge: Search in a 2D List

Solution: Search in a 2D List

Challenge: Search Position

Solution: Search Position

Challenge: Dutch National Flag Problem

Solution: Dutch National Flag Problem

Quiz on Sorting & Searching

Graph Algorithms

20 Lessons

Introduction to Graph Algorithms and Implementation

Challenge: Implement Breadth-First Graph Traversal

Solution: Breadth-First Graph Traversal

Challenge: Implement Depth-First Graph Traversal

Solution: Depth-First Graph Traversal

Challenge: Calculate the Number of Nodes in a Graph Level

Solution: Calculate the Number of Nodes in a Graph Level

Challenge: Transpose a Graph

Solution: Transpose a Graph

Challenge: Find All Paths Between Two Nodes

Solution: Find All Paths Between Two Nodes

Challenge: Check If a Graph is Strongly Connected

Solution: Check If a Graph is Strongly Connected

Challenge: Find All Connected Components in a Graph

Solution: Find All Connected Components of a Graph

Challenge: Remove an Edge

Solution: Remove an Edge

Challenge: Detect a Cycle in a Graph

Solution: Detect a Cycle in a Graph

Quiz on Graph Algorithms

Greedy Algorithms

12 Lessons

Greedy Approach: A Deep Dive

Challenge: Counting Money

Solution: Counting Money

Challenge: Connecting n Pipes With Minimum Cost

Solution: Connecting n Pipes With Minimum Cost

Challenge: Find the Egyptian Fraction's Denominators

Solution: Find the Egyptian Fraction

Challenge: Find the Minimum Platforms Required For a Station

Solution: Find the Minimum Platforms Required For a Station

Challenge: Find the Largest Number Possible

Solution: Find the Largest Number Possible

Quiz on Greedy Algorithms

Dynamic Programming

25 Lessons

Calculating Fibonacci Numbers

Introducing Dynamic Programming with Fibonacci Numbers

Memoizing Fibonacci Numbers

Tabulating Fibonacci Numbers

Challenge: The 0/1 Knapsack Problem

Solution: The 0/1 Knapsack Problem

Challenge: Staircase Problem

Solution: Staircase Problem

Challenge: The Partition Problem

Solution: The Partition Problem

Challenge: Longest Common Substring

Solution: Longest Common Substring

Challenge: Shortest Common Supersequence(SCS)

Solution: Shortest Common Supersequence(SCS)

Challenge: Longest Palindromic Subsequence

Solution: Longest Palindromic Subsequence

Challenge: The Coin Change Problem

Solution: The Coin Change Problem

Challenge: Egg Dropping Problem

Solution: Egg Dropping Problem

Challenge: Strings Interleaving

Solution: Strings Interleaving

Challenge: Edit Distance Problem

Solution: The Edit Distance Problem

Quiz on Dynamic Programming

Divide and Conquer

21 Lessons

Introduction to Divide and Conquer With Binary Search

Pascal's Triangle

Challenge: Euclidean Algorithm

Solution: Euclidean Algorithm

Challenge: Find the Peak Element

Solution: Find the Peak Element

Challenge: Maximum Sum Sublist of Size K

Solution: Maximum Sum Sublist of Size K

Challenge: Collect Coins in Minimum Steps

Solution: Collect Coins in Minimum Steps

Challenge: Find the Floor and Ceil of a Number in a Sorted List

Solution: Find the Floor and Ceil of a Number in a Sorted List

Challenge: Missing Number in a Sorted List

Solution: Missing Number in a Sorted List

Challenge: Find the Closest Number

Solution: Find the Closest Number

Challenge: Shuffle Integers

Solution: Shuffle Integers

Challenge: Inversion Count in a List

Solution: Inversion Count in a List

Quiz on Divide and Conquer

Conclusion

2 Lessons

Wrapping Up

Where to Go From Here

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Coderust

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Frequently Asked Questions

What are the common algorithms for Python?

The five most common algorithms for Python are as follows:

Sorting algorithms
Searching algorithms
Dynamic programming
Greedy algorithms
Recursion algorithms

How do I practice Python coding for an interview?

Beginner or advanced-level developers should take courses to study Python before their coding interview. Some areas to focus on should include algorithms, familiarity with Python’s standard libraries and data structures, and practicing their skills through coding challenges.

How to crack a Python interview

While preparing for your Python interview, you should invest more time learning key areas, such as Python’s key libraries, concepts such as time and space complexity, data structures and algorithms, etc. Take some time to go through Python courses and practice solving coding problems to test your skills regularly so you can track your progress.

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.

What algorithms should you know for coding interviews?

Essential algorithms for coding interviews include sorting (merge, quick, heap), searching (binary search), graph algorithms (BFS, DFS), dynamic programming (knapsack, longest common subsequence), and data structure-based algorithms (hashing, heaps, and trees).

Which sorting algorithm is the best choice in Python?

Python’s built-in sort() and sorted() use TimSort, a hybrid sorting algorithm combining merge sort and insertion sort. It’s highly efficient for real-world data, making it the best choice for most sorting tasks in Python.

How do I learn algorithms for coding?

Start by studying algorithm basics, solving problems on platforms like Educative, and practicing frequently. Focus on understanding core concepts like recursion, dynamic programming, and divide-and-conquer strategies, and gradually tackle more complex problems.

What algorithm should I learn first?

Start with basic sorting algorithms like bubble, selection, and insertion sort, then move on to more complex algorithms like merge sort, quicksort, and graph traversal algorithms like BFS and DFS.

How can I memorize algorithms easily?

Memorize algorithms by practicing regularly, solving problems multiple times, and understanding the underlying principles. Break down algorithms into smaller steps, visualize their workings, and implement them in different programming languages for better retention.