Often as a data scientist or data analyst, you will be collaborating with multiple people on the same project: you get assigned one part, a colleague gets assigned another part, and so on. Imagine that you were working on this project locally and uploaded the folder the project to a centralized location regularly. If you weren't very careful, it would be easy for someone making changes to their section of the project to overwrite changes someone else had made when this centralized file was updated.
Version control systems solve this problem. These systems will "merge" changes together intelligently, enabling multiple developers to work on a project at the same time. While there are few distributed version control systems, including Mercurial, Bazzar, and Git, Git is by far the most popular.
In this mission, you start learning and using Git. Git is a command-line tool we can access by typing
git in the shell. The first step in using Git is to initialize a folder as a repository, which tracks multiple versions of the files in the folder, enabling collaboration.
If you have heard of or used GitHub regularly, Github provides hosting for software development version control software using Git. Because GitHub uses Git, Git is paramount to learn as a data scientist. Not only will it assist you in a work setting but it'll aid you as you build a portfolio and establish your online presence. For more information about getting started on GitHub, you can follow our installation tutorial.
As you work through each concept, you’ll get to apply what you’ve learned from within your browser so that there's no need to use your own machine to do the exercises. The command line environment inside of this course includes answer checking so you can ensure that you've fully mastered each concept before learning the next concept.
1. Introduction to Version Control Systems
2. The .git Folder
3. Creating Files in the Repository
4. Checking File Status
5. Configuring Identity in Git
6. Committing Changes
7. Viewing File Differences
8. Making a Second Commit
9. Reviewing the Commit History
10. Viewing Commit Differences