Data science is becoming increasingly popular as industries continue to value its importance. Recent advancements in open source sofware have made this discipline accessible to a wide range of people. In this book, we show how Jupyter Notebooks can be used with Python for various data science applications. Aside from being an ideal "virtual playground" for data exploration, Jupyter Notebooks are equally suitable for creating reproducible data processing pipelines, visualizations, and prediction models. By using Python with Jupyter Notebooks, many challenges presented by data science become simple to conceptualize and implement. This is achieved by leveraging Python libraries, which offer abstractions to the more complicated underlying algorithms. The result is that data science becomes very approachable for beginners. Furthermore, the Python ecosystem is very strong and is growing with each passing year. As such, students who wish to continue learning about the topics covered in this book will fnd excellent resources to do so.By the end of this book, you will be equipped to analyse data using Python and use Jupyter notebooks effectively.