Preface

Data science has gain popularity in recent years. Harvard Business Review called it the Sexiest Job of the 21st Century. I am not sure whether it is sexy or not but one thing is sure is that data science subjects are very popular among university students. This can be seen from the course selection. Data science-related courses like Big Data, Machine Learning, Statistics, and algorithms have huge student enrollment numbers.

Data science is a multidisciplinary field. It blends data mining, data analysis, statistics, algorithm development, machine learning, and advanced computing and software technology together in order to solve analytically complex problems. Its ultimate goal is to reveal insight into data and get the data value for the business. It is obvious that gaining the related knowledge is essential but my observation is that a lot of students shy away from doing any data science projects is because they are lacking hands-on experience in any full cycle of doing a data science project.

There is a Chinese saying that “Practice makes perfect”. It is true but it is even more true that practices can gain the first hand of knowledge about practical issues and techniques to resolve the issues. Furthermore, it can build confidence in doing a data science project. That is what this book is intended to bring about.