AI Engineering Hub
MIT-licensed repository sorting 93 AI projects by difficulty (22 beginner, 48 intermediate, 23 advanced) and opening onto a ten-step roadmap: Python, Python for AI, maths for machine learning, understanding LLMs, research, agents, applied AI, MCP, project-based learning, books. Each step points to a free external course, Harvard CS50 for Python, the Andrew Ng course for AI in Python, Khan Academy playlists for the maths.
Strengths
- Projects sorted by difficulty, with one advanced family per major topic: a path reads at a glance
- Roadmap pointing to recognised free courses rather than in-house content
- MIT licence: you can start from the code of a project and make it yours
Limitations
- Many beginner projects are local demos that prove nothing to a recruiter
- No set order across the 93 projects: without the one-project-per-advanced-family advice, you scatter
- The repo also serves as a shop window for the paid newsletter of its author
Best for
- Working developer retraining toward AI engineering and looking for an order of work
- Tech lead building an AI upskilling path for the team