About

Data Science involves managing complicated multi-displinary projects that are highly likely to fail. There can be problems with expectations of what is achievable, moving goalposts, uncertainty around how to measure impacts and concern about the risk of doing something new.

Most data science courses ignore all of these topics and focus exclusively on technical skills and mathematical fundamentals. It is only when we start working on real-world data science projects that we discover the many additional complications that need to be navigated.

John Hawkins is a data scientist with a PhD in applied machine learning from the University of Queensland. He has been building, deploying and consulting on data science solutions across a range of projects in industry and academia for the past 16 years. Getting Data Science Done is the distillation of all this experience into a sequential guide to delivering pragmatic data science results.