Version control basics with git: Worked Example — Software and Environment Management (NVIDIA-Certified Associate: Accelerated Data Science)

Version Control Basics with Git: Worked Example for Accelerated Data Science

Version control is essential for managing changes in data science projects, ensuring reproducibility, collaboration, and traceability. Git is the most widely used version control system, and understanding its basic workflow is critical for the NVIDIA-Certified Associate: Accelerated Data Science certification.

Scenario

You are working on a GPU-accelerated data science project that involves developing a machine learning model. You want to track your code changes, collaborate with teammates, and maintain a clean project history.

Step-by-Step Git Workflow

1. Initialize a Git Repository

   Navigate to your project directory and initialize Git:

   • git init

   This creates a hidden .git folder that tracks changes.

2. Check Repository Status

   Check which files are untracked or modified:

   • git status

   This helps identify files to add to version control.

3. Add Files to Staging Area

   Stage files you want to commit. For example, add all Python scripts:

   • git add *.py

   The staging area prepares files for the next commit.

4. Commit Changes

   Commit staged files with a descriptive message:

   • git commit -m "Initial commit: added data preprocessing and model training scripts"

   This records a snapshot of your project.

5. Create a Remote Repository

   On a platform like GitHub or GitLab, create a remote repository to host your project.

6. Link Local Repository to Remote

   Connect your local repo to the remote URL:

   • git remote add origin https://github.com/USERNAME/REPO_NAME.git
7. Push Commits to Remote

   Upload your commits to the remote repository:

   • git push -u origin main

   This shares your work with collaborators and backs up your code.

8. Make Changes and Track Updates

   Modify your scripts to improve the model. Then repeat:

   • git add <changed_files>
   • git commit -m "Improved model accuracy by tuning hyperparameters"
   • git push
9. View Commit History

   To review project progress and changes:

   • git log

Summary

This workflow enables you to maintain a reproducible and collaborative environment for accelerated data science projects. Mastering these Git basics supports effective software and environment management, a key component of the NVIDIA-Certified Associate: Accelerated Data Science exam.

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