Doing Data Science: Straight Talk from the Frontline Book

Now that answering complex and compelling questions with data can make the difference in an election or a business model, data science is an attractive discipline. But how can you learn this wide-ranging, interdisciplinary field? With this book, you'll get material from Columbia University's Introduction to Data Science class in an easy-to-follow format. Each chapter-long lecture features a guest data scientist from a prominent company such as Google, Microsoft, or eBay teaching new algorithms, methods, or models by sharing case studies and actual code they use. You'll learn what's involved in the lives of data scientists and be able to use the techniques they present. Guest lectures focus on topics such as: Machine learning and data mining algorithms Statistical models and methods Prediction vs. description Exploratory data analysis Communication and visualization Data processing Big data Programming Ethics Asking good questions If you're familiar with linear algebra, probability and statistics, and have some programming experience, this book will get you started with data science. Doing Data Science is collaboration between course instructor Rachel Schutt (also employed by Google) and data science consultant Cathy O'Neil (former quantitative analyst for D.E. Shaw) who attended and blogged about the course.

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that's so clouded in hype?