/DataScience_Interview_Questions

My Solutions to 120 commonly asked data science interview questions.

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Data_Science_Interview_Questions

Introduction πŸ‘‹

Here are the answers to 120 Data Science Interview Questions

The above answer some is modified based on Kojin's original collection: kojino/120-Data-Science-Interview-Questions

Another solution is from: Nitish-McQueen: Data Science Interview Questions

Quera has a good list of questions: https://datascienceinterview.quora.com/Answers-1

Feel free to send me a pull request if you find any mistakes or have better answers.


Table of contents πŸ“‹

No. Name
01 01_120_Python_Basics_Interview_Questions
02 02_Predictive_Modeling
03 03_Programming
04 04_Probability
05 05_Statistical_Inference
06 06_Data_Analysis
07 07_Product_Metrics
08 08_Communication
09 09_Coding
10 10_Linkedin_Skill_Assessment_Python
11 DataScience_Interview_Questions

These are online read-only versions. However you can Run β–Ά all the codes online by clicking here ➞ binder


Frequently asked questions ❔

How can I thank you for writing and sharing this tutorial? 🌷

You can Star Badge and Fork Badge Starring and Forking is free for you, but it tells me and other people that it was helpful and you like this tutorial.

Go here if you aren't here already and click ➞ ✰ Star and β΅– Fork button in the top right corner. You will be asked to create a GitHub account if you don't already have one.


How can I read this tutorial without an Internet connection? GIF

  1. Go here and click the big green ➞ Code button in the top right of the page, then click ➞ Download ZIP.

    Download ZIP

  2. Extract the ZIP and open it. Unfortunately I don't have any more specific instructions because how exactly this is done depends on which operating system you run.

  3. Launch ipython notebook from the folder which contains the notebooks. Open each one of them

    Kernel ➞ Restart & Clear Output

This will clear all the outputs and now you can understand each statement and learn interactively.

If you have git and you know how to use it, you can also clone the repository instead of downloading a zip and extracting it. An advantage with doing it this way is that you don't need to download the whole tutorial again to get the latest version of it, all you need to do is to pull with git and run ipython notebook again.


Authors ✍️

I'm Dr. Milaan Parmar and I have written this tutorial. If you think you can add/correct/edit and enhance this tutorial you are most welcomeπŸ™

See github's contributors page for details.

If you have trouble with this tutorial please tell me about it by Create an issue on GitHub. and I'll make this tutorial better. This is probably the best choice if you had trouble following the tutorial, and something in it should be explained better. You will be asked to create a GitHub account if you don't already have one.

If you like this tutorial, please give it a ⭐ star.


Licence πŸ“œ

You may use this tutorial freely at your own risk. See LICENSE.