Onboarding Guide

Experiments with generative AI technologies in everyday IT engineering tasks

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Onboarding Guide

Welcome to the Learning AI project! This guide will help you get started with contributing to our generative AI experiments.

Getting Started

Prerequisites

Before you begin, make sure you have:

  • A GitHub account
  • Basic knowledge of Git and version control
  • Familiarity with at least one programming language (Python, JavaScript, VBA, etc.)
  • Interest in generative AI technologies and their applications

Setting Up Your Environment

  1. Fork the Repository: Start by forking our main repository

  2. Clone Your Fork: 
    git clone https://github.com/YOUR_USERNAME/learning_ai.git
cd learning_ai
  3. Install Dependencies: Depending on the project you’re working on, you may need to install:
    • Python 3.x and pip
    • Node.js and npm
    • Jekyll (for website development)
    • Other project-specific dependencies

Understanding Our Projects

Each project in our repository focuses on different aspects of AI-assisted development:

  • Administrative Automation: Tools for streamlining repetitive tasks
  • Workflow Automation: Scripts and applications for process optimization
  • Learning Tools: Educational resources and interactive experiments
  • Development Assistance: AI-powered coding and documentation tools

How to Contribute

1. Choose a Project

Browse our projects page to find something that interests you. Each project has its own documentation and contribution guidelines.

2. Start Small

Begin with:

  • Documentation improvements
  • Bug fixes
  • Small feature enhancements
  • Testing and validation

3. Communication

  • Join our discussions in GitHub Issues
  • Follow our coding standards and documentation practices
  • Ask questions when you need help

4. Submission Process

  1. Create a new branch for your work
  2. Make your changes with clear, descriptive commit messages
  3. Test your changes thoroughly
  4. Submit a pull request with a detailed description

Best Practices

Code Quality

  • Write clean, readable code with proper comments
  • Include tests when applicable
  • Follow existing code style and conventions
  • Document your changes and new features

AI Ethics and Responsibility

  • Consider the ethical implications of AI implementations
  • Ensure transparency in AI-generated content
  • Respect privacy and data protection guidelines
  • Contribute to responsible AI development practices

Collaboration

  • Be respectful and constructive in discussions
  • Share knowledge and learn from others
  • Contribute to a positive and inclusive environment
  • Help newcomers get started

Resources

Learning Materials

Development Tools

  • IDEs: VS Code, PyCharm, or your preferred editor
  • AI Assistants: GitHub Copilot, ChatGPT, or similar tools
  • Version Control: Git and GitHub
  • Testing: Project-specific testing frameworks

Community

Next Steps

  1. Explore the Codebase: Familiarize yourself with the repository structure
  2. Read Project Documentation: Each project has its own README and documentation
  3. Start Contributing: Pick an issue or suggest an improvement
  4. Join the Community: Participate in discussions and share your experiences

Questions?

If you have any questions or need help getting started:

  • Check the FAQ section
  • Create an issue with the “question” label
  • Reach out to the team through our contact page

Welcome aboard, and happy experimenting with AI! 🚀