Data Science Books

Even as more and more data becomes available, many of us have a view of the world that doesn't correspond to reality. On probabilities in particular, people tend to be completely clueless. Here Edouard Mathieu, Head of Data at Oxford-based research group Our World in Data, recommends books to help readers not only use data to better understand the world, but also make better decisions in daily life.

From complex techniques only used by academic statisticians, data science has risen to extreme popularity in only a few years. Roger D. Peng, Professor of Biostatistics at Johns Hopkins University and founder of one of the largest data science online courses, helps us understand this discipline and recommends the five best books to delve into it.

What do we mean when we talk about 'big data', and how can be become better critical consumers of it? Data scientist Vicki Boykis recommends the best books for learning Python—a language, she says, as versatile as a Swiss Army knife—and shows that it's possible to teach yourself coding and data science.

Data science is often said to be built on three pillars: domain expertise, statistics, and programming. Hadley Wickham, Chief Scientist at RStudio and creator of many packages for the R programming language, chooses the best books to help aspiring data scientists build solid computer science fundamentals.