AI Engineer Track
From foundations to LLM systems in production. RAG, agents, evaluation, cost, and safety.
- Anthropic
- OpenAI
- Cohere
- Google DeepMind
The five stages
- 1
Foundation
In progressPlain-English mental models — what an LLM is, how embeddings work, why RAG exists. Five concept pages, no code.
0 of 8 completed - 🔒
Core Skills
Submit boss to unlockChunking, retrieval, RAG fundamentals, token efficiency. Concept pages plus medium-difficulty problems.
Submit the Stage 1 boss to unlock - 🔒
Applied Practice
Submit boss to unlockRAG eval, agent architecture, cost optimisation, caching. Medium problems plus a blurred Pro concept tease.
Submit the Stage 2 boss to unlock - 🔒
Interview Ready
Submit boss to unlockFine-tuning vs RAG, multi-modal, monitoring, guardrails. Hard problems with golden-answer comparison.
Submit the Stage 3 boss to unlock - 🔒
Final Prep + Certificate
ProCompany-tagged problems only. Required 15-minute simulator capstone. Completion generates a shareable certificate.
Unlock with Pro