HomeCoursesData Structures for Coding Interviews in Python

Beginner

30h

Updated 1 month ago

Data Structures for Coding Interviews in Python

Explore proven strategies developed by FAANG engineers to ace coding interviews with a structured approach to data structures in Python. Prep faster with real-world questions.

Join 2.8M developers at

Pick a Language

C++

Java

JavaScript

Python

Pick a Language

Python

Overview

Content

Reviews

Data structures are amongst the most fundamental concepts of Computer Science. The data structure chosen can make or break an entire computer program. Consequently, they are also largely categorized as a vital benchmark of computer science knowledge when it comes to industry interviews. This course contains a detailed review of all the common data structures and provides implementation level details in Python to allow readers to become well equipped. Now with more code solutions, lessons, and illustrations than ever, this is the course for you!

Data structures are amongst the most fundamental concepts of Computer Science. The data structure chosen can make or break an en...Show More

Content

228 Lessons24 Quizzes65 Challenges

Introduction to Complexity Measures

22 Lessons

Sharpen your skills in evaluating the time and space complexity of algorithms.

Comparing Algorithms

Example: Measuring Time Complexity of For Loop

Example: Measuring Time Complexity of a Nested For 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

Introduction to Lists

26 Lessons

Unpack the core of lists and arrays in Python, and tackle essential list manipulation challenges.

Lists

Arrays

Lists vs Arrays in Python

Challenge: Remove Even Integers From List

Solution: Remove Even Integers From List

Challenge: Merge Two Sorted Lists

Solution: Merge Two Sorted Lists

Challenge: Find Two Numbers That Add Up to K

Solution: Find Two Numbers That Add Up to K

Challenge: Product of Array Except Self

Solution: Product of Array Except Self

Challenge: Find Minimum Value in List

Solution: Find Minimum Value in List

Challenge: First Non-Repeating Integer in a List

Solution: First Non-Repeating Integer in a List

Challenge: Find Second Maximum Value in a List

Solution: Find Second Maximum Value in a List

Challenge: Rotate List

Solution: Rotate List

Challenge: Rearrange Positive & Negative Values

Solution: Rearrange Positive & Negative Values

Challenge: Rearrange Sorted List in Max/Min Form

Solution: Rearrange Sorted List in Max/Min Form

Challenge: Maximum Sublist

Solution: Maximum Sublist

Lists Quiz: Test your understanding of Lists

Introduction to Linked Lists

30 Lessons

Examine the fundamentals, operations, and challenges of singly and doubly linked lists.

Introduction to Stacks and Queues

25 Lessons

Grasp the fundamentals of stacks and queues, their implementations, and practical challenges.

Introduction to Graphs

26 Lessons

Dig into graph concepts, representations, algorithms, and their practical applications in coding.

Introduction to Trees

38 Lessons

Focus on trees' structures, properties, and traversal methods, covering binary, AVL, and Red-Black Trees.

Trie

14 Lessons

Build on understanding trie structures, their operations, and solving challenges using them.

Introduction to Heap

12 Lessons

Learn how to use heaps for efficient sorting, priority queues, and element retrieval.

Introduction to Hashing

33 Lessons

Walk through hash table fundamentals, efficient operations, implementation strategies, and algorithmic challenges.

10.

Summary of Data Structures

2 Lessons

Examine linear and non-linear data structures, their complexities, and practical applications.

Data Structures

Mock Interview

Premium

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Coderust

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

"These are high-quality courses. Trust me. I own around 10 and the price is worth it for the content quality. EducativeInc came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks"

Anthony Walker

@_webarchitect_

"Just finished my first full #ML course: Machine learning for Software Engineers from Educative, Inc. ... Highly recommend!"

Evan Dunbar

ML Engineer

"You guys are the gold standard of crash-courses... Narrow enough that it doesn't need years of study or a full blown book to get the gist, but broad enough that an afternoon of Googling doesn't cut it."

Software Developer

Carlos Matias La Borde

"I spend my days and nights on Educative. It is indispensable. It is such a unique and reader-friendly site"

Souvik Kundu

Front-end Developer

"Your courses are simply awesome, the depth they go into and the breadth of coverage is so good that I don't have to refer to 10 different websites looking for interview topics and content."

Vinay Krishnaiah

Software Developer

Hands-on Learning Powered by AI

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

Personalized Interview Prep

Skip the LeetCode grind with a custom roadmap that adapts to your goals. Hands-on practice for Coding Interviews, System Design, and more.

Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

AI Prompt

Build prompt engineering skills. Practice implementing AI-informed solutions.

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.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

Course

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.

15 h

intermediate

Course

Decode the Coding Interview in Python: Real-World Examples

The ultimate guide to coding interviews in Python: Strategies developed by FAANG engineers. Prep faster with real-world problems, get interview-ready in just a few hours.

15 h

beginner

Course

Learn Functional Programming in Python

Gain insights into functional programming in Python, learn about functions as objects, recursion, closures, and generators, and discover how to confidently apply these concepts to your projects.

5 h

beginner

Course

Python for Mechanical and Aerospace Engineering

Gain insights into using Python for mechanical and aerospace engineering. Learn about basics, graphing techniques, airfoil plotting, and dynamic pressure and orbital modeling in 2D and 3D.

8 h

beginner

Course

Grokking Bit Manipulation for Coding Interviews

The ultimate guide to bit manipulation for coding interviews. Developed by FAANG engineers, practice with real-world interview questions, and get interview-ready in just a few hours.

3 h

intermediate

Course

Coderust: Hacking the Coding Interview

The ultimate guide to coding interviews. Developed by FAANG engineers, practice with real-world questions in top languages. Prep faster and get interview-ready in just a few hours.

40 h

beginner

Course

Predictive Data Analysis with Python

Learn predictive data analysis with Python using NumPy, Pandas, Matplotlib, and Seaborn. Apply skills to real-world finance and advertising projects to extract and visualize insights.

10 h

beginner

Course

Algorithms for Coding Interviews in Python

intermediate

15 hour

Course

Decode the Coding Interview in Python: Real-World Examples

beginner

15 hour

Course

Learn Functional Programming in Python

beginner

5 hour

Course

Python for Mechanical and Aerospace Engineering

beginner

8 hour

Course

Grokking Bit Manipulation for Coding Interviews

intermediate

3 hour

Course

Coderust: Hacking the Coding Interview

beginner

40 hour

Course

Predictive Data Analysis with Python

beginner

10 hour

Free Resources

Frequently Asked Questions

What are the data structures for coding interviews in Python?

For coding interviews in Python, focus on these essential data structures:

Lists: Used for dynamic arrays that support fast access, insertion, and deletion.
Dictionaries: Implement hash tables for efficient key-value storage and lookups.
Sets: Store unique elements and provide fast membership checks.
Tuples: Immutable sequences used for fixed-size collections.
Queues and stacks: Use collections.deque for double-ended queues, which can also efficiently implement stacks and queues.
Heaps: Use heapq for priority queues.
Linked lists, trees, and graphs: Implement manually using classes to handle more complex problems.

Mastering these structures and their operations will prepare you well for Python coding interviews.

Can I use Python for DSA in an interview?

Yes, you can use Python for DSA in interviews. Python is highly popular for its simple syntax, readability, and powerful built-in libraries, which make implementing data structures and algorithms easier. It offers built-in support for lists, dictionaries, sets, and other data structures, along with libraries like collections and heapq for more advanced needs. Python’s versatility and ease of use make it a great choice for demonstrating problem-solving skills in interviews.

How to prepare for a coding interview in Python

To prepare for a coding interview in Python, focus on mastering key data structures (like lists, dictionaries, sets, and heaps) and algorithms (such as sorting, searching, and dynamic programming). Practice solving problems on platforms like LeetCode or HackerRank to build familiarity with Python’s syntax and libraries. Understand time and space complexities and review Python-specific features like list comprehensions, generator expressions, and built-in functions. Regularly simulate coding interviews to improve your problem-solving speed and communication skills.

Is Python a good choice for coding interviews?

Yes, Python is an excellent choice for coding interviews. Its clean and concise syntax allows you to write and debug code quickly, making it ideal for solving complex problems under time constraints. Python’s extensive standard library provides built-in data structures (like lists, dictionaries, and sets) and algorithms, which help simplify implementations. It’s widely accepted in interviews across various companies, and many interviewers are familiar with its capabilities, making it a strong option for effectively demonstrating problem-solving skills.

What are the five data types in Python?

The five primary data types in Python are as follows:

Integers (int): Represent whole numbers, such as 1, 42, or -7.
Floating-point numbers (float): Represent decimal numbers, such as 3.14, 0.001, or -2.5.
Strings (str): Represent sequences of characters, such as “hello”, “Python”, or “123”.
Booleans (bool): Represent truth values, either True or False.
NoneType (None): Represents the absence of a value or a null value, expressed as None.

These basic data types form the foundation for handling and manipulating data in Python.

HomeCoursesData Structures for Coding Interviews in Python

Learn in-demand tech skills in half the time