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Interactive 3D/AI Learning Path Graph
Math
Code
ML
LLM
AI Engineering
MLOps
Data
prerequisites
unlocks
AI Learning Path
Click any topic to see its prerequisites and what it unlocks.
Target Role
12 topics highlighted for AI Engineer. Dimmed topics are optional for this role.
How to read this
Topics with arrows pointing to them have prerequisites. Start with Python and Math, then ML Basics, then specialize.
Critical path to AI Engineer:
Python → NumPy → ML Basics → Neural Nets → Attention → Transformers → LLM Fundamentals → RAG / Agents
Modules
Math
Code
ML
LLM
AI Engineering
MLOps
Data

AI Learning Path Graph - Interactive Visualization

Every advanced AI topic has prerequisites, and learning them out of order wastes months. This force-directed graph maps 20 core topics - from Python and Linear Algebra through Transformers and RAG - and shows which must come before which. Click any node to see what unlocks it and what it unlocks. Select a target role to highlight only the topics on your critical path.

  • 20 core topics spanning Math, Coding, ML, LLMs, AI Engineering, and MLOps
  • Prerequisite edges: directed arrows show what you must know first
  • Click any node: see prerequisites (green) and what this topic unlocks (orange)
  • Role filter: highlight only the topics needed for ML Engineer, AI Engineer, or MLOps roles
  • Force-directed physics simulation: related topics cluster naturally together
  • Use as a planning tool: start at the bottom (Python, Math), work upward toward your target

Part of the EngineersOfAI Interactive 3D - free interactive visualizations covering every major concept in machine learning and AI engineering. Hover any element for a plain-English explanation. No code required.