Data Science Workflow with Git and GitHub focuses on managing and organizing data science projects using version control systems. Git is used to track changes in code, datasets, and experiments, while GitHub provides a collaborative platform for sharing and maintaining projects. This training explains how to structure data science workflows, create repositories, manage branches, and handle version history effectively. It also covers collaboration practices such as pull requests, code reviews, and issue tracking. You will learn how to maintain reproducibility in data science projects and collaborate efficiently with teams. The course also highlights best practices for project organization, experiment tracking, and deploying data science workflows in real-world environments.
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