Data science in practice Data Science in Practice is the ideal introduction to data science. With or without math skills: Here you get the all round view that you need for your projects. This book describes how to properly question data in order to unearth the treasure that data can be. You will get to know the relevant analysis methods and will be introduced to the programming language R which is ideally suited for data analysis. Associated tools like notebooks that make data science programming easily accessible are included in this introduction. Because technology alone is not enough this book also deals with problems in project implementation illuminates various fields of application and does not forget to address ethical aspects. Data Science in Practice includes many examples notes on errors decision making aids and other practical tips. This book is ideal as a complementary text for university students and is a useful learning tool for those moving into more data related roles Machine learning data science and artificial intelligence The anatomy of a data science project Introduction to R Exploratory data analysis Forecasting Clustering Classification Other use cases Workflows and tools Ethical handling of data and algorithms Next steps after this book