Data Science Resources

These are data science resources that I used and I highly recommend:
(Most of these are free!)

Databases:

Introduction to Databases by Jennifer Widom

  1. Always available so you don’t have to wait for a session to start and self-paced.
  2. Databases is a core skill that must be mastered in order to be any sort of data user

Statistics and probability:

Think Stats – Probability and Statistics for Programmers by Allen B. Downey

brilliant.org (subscription)

  1.  This is a paid subscription service, but this is worth the $$!  You will not find a fun, interactive way of learning like brilliant.org
  2. Emphasis on combinatorics page, but the other lessons are worth learning as well

Machine learning:

Stanford University Machine Learning course by Andrew Ng

  1. This course is a must for anyone itching to learn ML, Andrew gives a complete and free course on Machine Learning with examples and hands-on excercises

SQL:

Stanford University’s DB5 SQL

  1. A solid SQL class that compliments Introduction to Databases by Jennifer Widom

SQLcourse2.com 

  1. Recommended by Facebook Data Science interview guide

SQL Zoo

  1. Offers both SQL problems and a self paced tutorial
  2. The problems offered here are probably the most analogous to what will be asked in the interview

W3 Schools

  1. Offers a slowly paced, broadly scoped tutorial
  2. Covers more topics than SQLZOO but is less challenging
  3. Recommended on Facebook’s Data Science Interview guide

Active SQL

  1. Offers SQL exercises sequenced according to complexity
  2. Recommended on Facebook’s Data Science Interview guide

Python Development:

Dive into Python 3

Basic Practice

More Mathematical (and Harder) Practice

List of Practice Problems

A SubReddit Devoted to Daily Practice Problems

Python coding puzzle challenge

  1. I love puzzles!!!! So, I highly recommend this.  If you find puzzles fun, you will have a great time going through these puzzles and it will help improve your python skills.

Python for Data Science (Pandas, Numpy, etc):

Python Data Science Handbook

  1. A very well written book on how to use iPython (Python for data science)
  2. This book will give you all you need to know on how to use python libraries

Data Science from Scratch: First Principles with Python

  1. I haven’t checked out this resources yet, but I plan to do so

Python for Data Science and Machine learning bootcamp by Jose Portilla (Paid)

  1. A hands on tutorial and step by step tutorial on how to use python for DS
  2. Jose Portilla’s classes on Udemy are a good way of learning Data Science basics and he is a great instructor

Interview Guides and practice:

Practice programing interview questions

  1. Recommended on Facebook’s Data Scientist interview guide

HackerRank

  1. A great place to practice technical questions
  2. Challenges available to help improve your technical abilities
  3. Practice questions are labeled by difficulty

Leetcode

  1. Leet code offers very similar questions that may be asked in a technical interview

Algorithms:

Cracking the Coding Interview 6th Edition

  1.  A MUST READ,  this book will be your best friend in preparing you for the coding interviews

Growth and Product knowledge:

Alex Schultz presentation – VP of Growth (Facebook) 

  1. A quick 40 minute presentation from Facebook’s VP of growth, watch this to better understand product and growth

Programming and Computer Science:

CS50’s Introduction to Computer Science – Harvard edX

  1. Not directly related to Data Science, but this course helped me with programming and algorithms

But wait… there’s more!

I introduce you the biggest database of data resources:

Data Science Massive Resource Center

  1. Not all of these resources are free, but feel free to look the list
  2. This table is sortable, so you easily find the resources that you are looking for