Git Version Control Tutorial
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Updated
Apr 17, 2023
Git Version Control Tutorial
An interactive Command Line Interface (CLI) tool that helps break existing Git commits and reorganize them into new commits.
A Repository created for emerging Java Developers to contribute by solving some of the problems which enhance their learning and also adds on to their contributions on github, thus providing a taste of what contributing and working on something opensource feels like.
This repository contains all the basic needed for working with git & github using Command-Line or SourceTree gui
A passionate and dedicated Software Developer with over 3 years of experience in the industry. I hold a Diploma degree in Computer Science and specialize in building websites, both static and dynamic, with expertise in Python and the Django framework. My focus is on delivering
A minimal version control system implemented in C that demonstrates the core concepts of version control. MVCS supports repository initialization, object storage (blob/tree/commit), SHA-256 hashing, staging area, commits, and history traversal.
The Codeial Development project is a social media web application built with the MERN stack, featuring user authentication using Passport.js and JWT-based tokens. It supports profile picture uploads with Multer and utilizes AJAX for dynamic updates. Secure RESTful APIs, tested via Postman, handle backend operations, API integerations and frontend.
This is a workshop project organized by the Abuja R Users Group in Nigeria.
This repository contains my solutions to various Linux Shell scripting challenges from HackerRank. Organized by topic, these scripts demonstrate practical use of commands like `head`, `awk`, `sed`, loops, conditionals, and more. Each script includes comments to illustrate my approach and learning process.
version control for engineers (using git)
Introduction to Basic Git Commands and their Usage
A Go-based version control system designed specifically for tracking changes in datasets (CSV, JSON, binary blobs) with content deduplication and metadata-aware diffs. Built for reproducibility in scientific and machine learning research. Version control for datasets, not code.
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