50+ interviews worth of comprehensive data science resources
Data science interviews certainly aren’t easy. I know this first hand. I’ve participated in over 50 individual interviews and phone screens while applying for competitive internships over the last calendar year. Through this exciting and somewhat (at times, very) painful process, I’ve accumulated a plethora of useful resources that helped me prepare for and eventually pass data science interviews. Long story short, I’ve decided to sort through all my bookmarks and notes in order to deliver a comprehensive list of data science resources. With this list by your side, you should have more than enough effective tools at your disposal next time you’re prepping for a big interview.
I wrote a Medium post on the experience as well. You can find the post and more about my experience here:
The Big List of DS/ML Interview Resources
- Interview Q&A bank
- Tech Interview Handbook
- Best Data Science Courses Online
- What it’s like to be on the data science job market
- Learn Data Science on Quora
- Tips for Data Science Interviews on Quora
- How do I prepare for a phone interview with Airbnb?
- Emily Robinson Advice Applying to Data Science Jobs
- Two Sides of Getting a Job as a Data Scientist
- Robert Chang Doing Data Science at Twitter
- Questions I’m Asking in Interviews
- Creating a Great Data Science Resume
- Data Science Interview Guide
- 3 Types of Data Science Interview Questions Joma Tech
- How to Land a Data Scientist Position at Airbnb
- Red Flags In Data Science Interviews
- Advice Building out a Portfolio
- Youtube William Chen Resume/Portfolio Tips
- How to Prepare for Data Science Interviews Quora Answers
- 120 Data Science Questions Answers
- Analytics Vidhya Comprehensive Interview Resources
- Dataquest Data Science Career Guide
- Notes and technical questions from interviewing as a Data Scientist in 2018
- Mastering the Data Science Interview Loop
- Time complexity in Python
- Leetcode
- Stacks and queues in Python
- Preparing for Programming Interviews with Python
- Coding Interview University on Github
- Philip Guo Programming Interview Tips
- Google Python Style Guide
- Algorithms in Python Github
- Intro to Classes and Objects in Python
- Coding Interview Github Compilation
- Problem Solving with Data Structures & Algorithms in Python
- Python Leetcode Video Series Nasr Maswood
- Python Tricks and Tips
- Big List of Interviewee Interview Questions
- Basics of Probability for Data Science
- William Chen Probability Cheatsheet
- 40 Questions on Probability for Data Science Interviews
- Common Probability Distributions
- Probability and Statistics for DS Medium Series
- Mode Tutorial
- How to Ace Data Science Interviews: SQL
- How to Write Better Queries (Datacamp)
- Practice SQL problems
- 10 Frequently Asked SQL Questions
- 45 Essential SQL Interview Questions
- More SQL practice on Github
- Data School Video Series
- Intro to Pandas Data Strutures
- Excel Tasks in Pandas
- Data Analyst Interview Practice Checkist Udacity
- More Pandas Exercises on Github
- Machine Learning in Python Github Repo
- The Applied Machine Learning Process
- Springboard 41 Essential Machine Learning Questions
- Data School 15 Hours of Machine Learning Videos
- Difference between boosting and bagging
- Comprehensive Guide to Ensemble Learning Analytics Vidhya
- Kaggle Data Science Glossary
- Machine Learning Interview Checklist Udacity
- Google Machine Learning Glossary
- 100 Days of ML Code Infographics
- Machine Learning for Dummies Algorithm Overview
- ML Algorithm Pros and Cons
- Advantages of Different Classification Algorithms
- The MLInterview Repo
- Experiments at Airbnb
- When Should A/B testing not be trusted?
- TutorialsPoint A/B testing questions
- Udacity A/B Testing Course
- Summery of Udacity A/B Testing Course
- Hubspot Frequently Asked Questions about A/B Testing
- Introduction to Churn in Python
- How Do You Set Metrics? - Julie Zhou
- Metrics vs. Experience - Julie Zhou
- How Not to Run an A/B Test
- 12 Guidlines for A/B Tests
- A/B Testing at Stack Overflow
- Type I vs. Type II Errors Simplified
- A/B Testing TutorialPoint
- Case Study: Pay as You Go
- 27 Metrics Used at Pinterest
- 70 Resources to Get Started With A/B Testing
- Apache Spark in Python: Beginner’s Guide (Datacamp)
- Apache Spark vs. Mapreduce Whiteboard Walkthrough
- Differences Between Hadoop and Spark
- What is Hadoop?: SQL Comparison
- Data Engineering Interactive Map
- How to Learn Apache Spark? Quora Post
- Youtube Intro to Big Data with PySpark
- Spark Documentation Screencasts
- PySpark Cheatsheet