The final chapter focuses on two fundamental topics in data science: ethics and reproducibility. Ethics and reproducibility are defined, emphasizing their importance in data handling. The principles of information ethics are examined, along with their connections to law, morality, and common sense. Examples of how different countries regulate personal information are provided to offer a global perspective. Key elements and best practices for ensuring reproducibility in research are outlined to reinforce the importance of transparent and repeatable methodologies. The second part introduces practical implementation using RStudio to create a project with Git. The process begins with setting up a GitHub account, creating a new repository, and installing Git on Windows or Mac. Subsequently, practical exercises include using “commit” and “push” commands to update the project on GitHub.