Start Here14 DaysBeginner
Phase 0 — Foundation & Tooling
Set up your full AI development environment and build mental models of the AI landscape before writing a single model line of code.
- Configure a reproducible Python environment with version control.
- Understand the difference between AI, ML, DL, and GenAI.
- Discover the core platforms: Kaggle, Hugging Face, Colab.
⚡ Must Know
- Python Setup — install + verify
- VS Code + Extensions — Python, Jupyter, GitLens
- Jupyter Notebooks — cells, markdown, kernel
- Git & GitHub — init, add, commit, push
- Virtual Environments — venv or conda
- pip / Package Management — install, freeze, requirements.txt
- Command Line Basics — cd, ls, mkdir, mv
- AI/ML/DL/GenAI — distinctions — know what each solves
✨ Good to Know
- Google Colab + GPU
- Kaggle Platform
- Hugging Face Hub
- Anaconda Distribution
- WSL2 (Windows users)
📚 Resources
🏗️ Projects
Dev Environment Setup
Set up Python, notebooks, and Git so every later AI project is reproducible.
AI Landscape Mind Map
Visual map linking AI domains, problems, models, and real-world use cases.