As I'm working through my own self-powered education in data science I'll post useful links here with thoughts on the content and notes on my own progress.
Maybe you have a mac. Lucky you. I have a PC and decided to dual boot Ubuntu. It's another learning curve but has been worth it. Develop in Windows at your own peril (jk... kind of).
R and Python are both sufficiently mature and thriving to support your data science ambitions. Ideally you'll be familiar and fluent in both as each has its advantages. I'm ignoring that advice, however, and focusing on Python right now.
Databases and SQL
Data Assessment and Cleansing
Data Mining and Text Analysis
Visualization - Basic
In Python, pandas has some basic plotting functionality and is a good place to start when working with a dataset. Matplotlib goes beyond this, allowing for some R-worthy segmentation.
Visualization - Maps & Interactive
Visualization - Advanced
Machine Learning - Supervised
Machine Learning - Unsupervised