Git & Version Control
Git & Version Control on AI-ML Companion: Essential version control skills for collaborative AI development. 17 interactive modules with live visualizations, quizzes, and hands-on Python coding.
Modules in this track
- What is Git? - Version control concepts and why Git matters
- Git Setup & Configuration - Installing Git, SSH keys, and global config
- Git Basics - init, add, commit, status, log - the core commands
- .gitignore Mastery - Ignoring files: patterns, templates, and ML-specific rules
- Writing Good Commits - Atomic commits, messages, and conventional commits
- Working with Remotes - Push, pull, fetch, and remote repositories
- GitHub Essentials - Repositories, issues, and GitHub features
- When Git Goes Wrong - Reading Git errors, auth failures, line endings, and OS-specific fixes
- Branching & Merging - Creating branches, merging, and branch strategies
- Merge Conflicts - Understanding and resolving conflicts
- Pull Requests & Code Review - PR workflow, reviews, branch protection, and automated checks
- Undoing Changes - Reset, revert, restore - recovering from mistakes
- Navigating History - Log options, blame, bisect - finding bugs and understanding changes
- Tags & Releases - Tagging versions, semantic versioning, and shipping GitHub Releases
- Git Workflows - GitFlow, trunk-based development, and team patterns
- Advanced Git - Rebase, cherry-pick, stash, and reflog
- Git LFS for ML - Managing large files, models, and datasets