- First and foremost, this is a personal account. If things pan out differently for you, that's just great; we are all different. This advice will best suit Physicists. As a demographic, we have our particular ways of thinking that might not suit everyone.
- The full set of material that could reasonably be in the scope of data science jobs is huge (more on that later). I hope the following will help you in your search for the foundational material, that is a shortcut I can offer you. However, you should still be prepared to put in a lot of hours working through this material in your own time.
Understand the Big Picture
- Chomsky on where AI went wrong
- On Chomsky and the two cultures of statistical learning (a riposte by Peter Norvig to the above)
- The End of Theory
- The Unreasonable Effectiveness of Data
Not all Data Scientist Roles are equal
Learn Python or R
- Matplotlib for plotting
- NumPy for numerical and matrix operations
- SciPy for fitting, optimisation and other common operations
- Scikit-learn for machine learning, fitting and classification operations
- Pandas for time series capabilities (Greg Reda has a good intro)
- IPython is a fantastic, rich interactive environment for Python
The relative merits of each are discussed in more detail here. As a biased Pythonista, I would also point out that Python is now the official teaching language of MIT.
I Studied X, Can I Become a Data Scientist?
Start a Pet Project
Learn to Communicate
Get Acquainted with End-to-End Development
- Startup Engineering (Coursera)
- Web Development (Udacity)
- Why Becoming a Data Scientist is Not as Easy as You Think (in response to this optimistic article)