AI Engineering Learning Paths
Choose your role and get a structured, curated path with guides, projects, and milestones tailored to that career track.
AI Engineer Learning Path
A complete roadmap to becoming an AI Engineer — the generalist role that designs, builds, and ships AI-powered applications and systems in production.
AI Product Engineer Learning Path
Bridge product thinking and AI engineering — the AI Product Engineer path covers building user-facing AI features, designing great AI UX, and shipping AI products end to end.
AI Research Engineer Learning Path
Go deep on the science of AI — the AI Research Engineer path covers mathematical foundations, novel architectures, paper implementation, and contributing to the frontier of AI research.
LLM Engineer Learning Path
Master large language models from the inside out — the LLM Engineer path covers transformer architecture, fine-tuning, inference optimization, and deploying custom models at scale.
ML Engineer Learning Path
From data to deployed models — the ML Engineer path covers the full machine learning lifecycle: data pipelines, model training, evaluation, MLOps, and production serving.