This document discusses data science and provides examples. It begins by asking what data science is besides an excuse for food and drinks. It then discusses hacking skills like bash/awk/sed and statistics concepts like probability. Domain expertise and intelligence are also important. The document presents an "intelligence cookbook" approach of first making a solution valuable, then possible, then beautiful, and finally smart. Common machine learning problems and approaches are listed. The document concludes that real data science is hard but should focus on the business problem, not just the science. It provides contact information for questions.