Introduction to Data Science

Data science is a thriving and rapidly expanding field, as you probably already know. People are starting to come to a consensus that everyone should have some basic data science skills, sometimes called "data literacy." This book is intended to get you up to speed with the basics of data science using the most popular programming language for doing data science today: Python. In this first chapter, we will cover:

• The history of data science
• The top tools and skills used in data science, and why these are used
• Specializations within and related to data science
• Best practices for managing a data science project

Data science is used in a variety of ways. Some data scientists focus on the analytics side of things, pulling out hidden patterns and insights from data, then communicating these results with visualizations and statistics. Others work on creating predictive models in order to predict future events, such as predicting whether someone will put solar panels on their house. Yet others work on models for classification; for example, classifying the make and model of a car in an image. One thing ties all applications of data science together: the data. Anywhere you have enough data, you can use data science to accomplish things that seem like magic to the casual observer.