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A practical Git walkthrough for data scientists, focused on real workflows like branching for experiments, reverting mistakes, and keeping project history clean with small, focused commits. It also explains merge vs. rebase, why you should not rebase shared branches, and how to set up .gitignore for data-heavy projects.