How to Learn Data Science (On the Cheap)

My name is Nik and I created this blog as a way to chronicle my cross-career journey (descent?) into data science and Big Data. One of the biggest questions when I started was “Where do I even begin?” I figure there’s others like me out there, so I’ve compiled this list of resources to help us out. Let me know if you know of any others!

101 – Start Here

1. An Introduction to Data Science by Jeffrey Stanton, Syracuse University
   
2. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
3. Harvard University Extension School’s Data Science Course
4. Statistics in a Nutshell (In a Nutshell (O’Reilly))

201 – Wax On / Wax Off

1. Mining of Massive Data Sets by Anand Rajaraman and Jeff Ullman, Stanford University
2. Elements of Statistical Learning by Hastie, Tibshirani, Friedman, Stanford University
3. Learn R & Become a Data Analyst (Datacamp Course)

301 – Life Lessons

1. Kaggle Competitions
2. Building Machine Learning Systems with Python
3. Analyzing Big Data With Twitter (Berkeley Course)
4. Natural Language Processing with Python

401 – Semi-Finals

1. NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence
2. Intro to Hadoop and Mapreduce
3. Programming Collective Intelligence: Building Smart Web 2.0 Applications
4. How You Should Go About Learning NoSQL

501 – Sweep the Leg

1. Harvard University Extension’s Data Visualization Course
2. Probabilistic Programming and Bayesian Methods for Hackers
3. Artificial Intelligence (BerkeleyX)