- Organize the repository structure and set up a README file outlining the project's purpose and guidelines.
- Create a folder structure for each day's exploration, ensuring consistency and easy navigation.
- Research and brainstorm a list of 100 AI topics to cover throughout the journey.
- Write a brief overview and code examples for each topic, providing a comprehensive understanding of the concepts.
- Compile a curated list of research papers, articles, and online resources related to each topic.
- Develop tutorials with step-by-step instructions and exercises to reinforce learning.
- Gather and prepare diverse datasets suitable for various AI applications and share them within the repository.
- Implement code examples in popular AI frameworks like TensorFlow or PyTorch, ensuring compatibility across different versions.
- Create cheat sheets summarizing key algorithms, frameworks, and terminology for quick reference.
- Encourage users to contribute their AI projects, providing instructions for submission and showcasing selected projects.
- Periodically review and update the existing content, fixing any bugs or errors and incorporating user feedback.
- Engage with the AI community, respond to inquiries, and provide support to ensure a vibrant and inclusive learning environment.
- Create video tutorials or screencasts for complex topics, catering to different learning preferences and enhancing the multimedia learning experience.