Resources for Data Science Interviews

On whence someone asked me “now that I am finished with class, what books should I read and videos should I watch in order to learn more about this field?” and I answered “get ready to drink from the firehose.”

Data Science Resources

In no particular order but the math is the most helpful


  • If you haven’t already read ISLR, start there. Book Link
  • Practical Statistics for Data Science Amazon Link

Linear Algebra

  • Udacity’s Linear Algebra Refresher
  • YouTube:
    1. MIT 18.06 Linear Algebra with Gilbert Strang
    2. MIT 18.S096 Topics in Math… Finance
    3. Econometrics 421
  • Books:
    1. No B.S. Guide to Linear Algebra
  • FastAi
    1. Computational Linear Algebra Course

Computer Science

  • YouTube:
    1. MIT 6.006 Intro to Algorithms
    2. Khan Academy Algorithms
  • Udacity:
    1. Data Structures and Algorithms
    2. Intro to Algorithms
  • Books:
    1. Think Complexity
    2. Crack the Coding Interview


  • YouTube:
    1. Stanford CS 224N
  • Books:
    1. Natural Language Processing with PyTorch

Deep Learning and ML Stuff

  • Books:
    1. Hands on Machine Learning with SciKit-Learn and Tensorflow
    2. Data Science from Scratch
    3. Deep Learning
    4. Elegant SciPy
    5. Data Science at the Command Line
  • Udacity:
    1. Deep Learning Nanodegree
  • Udemy:
    1. PyTorch for Deep Learning

Data Science Periphery

  • Books:
    1. Docker for Data Science
    2. Apache Spark: The Definitive Guide
    3. Kafka: The Definitive Guide
    4. Kubernetes Up and Running
  • Udemy:
    1. The Ultimate Hands On Guide to Hadoop
    2. Build a SaaS app in Flask

Learning R for Pythonistas

Written on January 2, 2020