Git Intermediate Techniques
1h 44mIntermediate2022-11-14
Authors

Kevin Skoglund
Founder of NovaFabrica
Course details
Enhance your Git skillset, and explore intermediate techniques and concepts that can help you work more efficiently with the popular open-source version control software. Instructor Kevin Skoglund shares branch management techniques, like deleting and pruning, and how to use tags to mark important points in the branch history. Learn to use interactive staging to stage small portions of a file, cherry-picking to share commits between branches, patches to share commits with others, and techniques for tracking down problems in your project. Kevin demystifies the rebase command and explains when to choose rebasing over merging.
Skills covered
GitVersion ControlDevOps ToolsDevOpsOpen SourceSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - Get more from Git
- 02 - Using the exercise files on GitHub
1. Branch Management
- 03 - Force push to a remote
- 04 - Identify merged branches
- 05 - Prune stale branches
2. Tagging
- 06 - Create and delete tags
- 07 - List tags
- 08 - Push tags to a remote
3. Interactive Staging
- 09 - Interactive mode
- 10 - Patch mode
- 11 - Split a hunk
- 12 - Edit a hunk
4. Share Select Changes
- 13 - Cherry-picking commits
- 14 - Resolve cherry-picking conflicts
- 15 - Create diff patches
- 16 - Apply diff patches
- 17 - Create formatted patches
- 18 - Apply formatted patches
5. Rebasing
- 19 - Rebase commits
- 20 - Perform a rebase
- 21 - Merging vs. rebasing
- 22 - Interactive rebasing
- 23 - Squash commits
- 24 - Pull rebase
6. Track Down Problems
- 25 - Log options
- 26 - Blame
- 27 - Bisect
Conclusion
- 28 - Next steps
Related courses
Related learn paths
- Get Started with PHP
- Continuous Integration/Continuous Delivery (CI/CD) with Jenkins
- Become a Full-Stack Web Developer
- Software Development Fundamentals
- Network Automation Professional Certificate by Arista Networks
- Explore Web Development with Node.js
- Succeed as a Remote Software Developer
- Working with Data: Engineering, Integration, and MLOps for AI