Role specialisation tracks

Stage D. Each track is 160 hours of role depth across four modules plus a track project, taken to production standard. Learners choose one.

R1 · AI Engineer

160 h

Highest 2026 demand — builds and operates production AI features

PythonFastAPILangChainLangGraphLlamaIndexpgvector+7
Anchor track

R2 · GenAI / LLM Engineer

160 h

Highest-paid specialisation — adapts, serves and evaluates models

PyTorchHugging Face TransformersDatasetsPEFTTRLbitsandbytes+5

R3 · MLOps / LLMOps Engineer

160 h

9.8× posting growth — owns the path to production

DockerKubernetesHelmMLflowDVCAirflow+5

R4 · Data Scientist

160 h

Strongest official growth signal — BLS +34% to 2034

PythonSQLscikit-learnXGBooststatsmodelsSHAP+4

R5 · Data & RAG Engineer

160 h

The retrieval data layer every AI system depends on

PythonSQLAirflowdbtUnstructuredpgvector+4

R6 · AI Solutions Architect

160 h

Advanced track — designs systems that hold up commercially and legally

AWS BedrockAzure AIGoogle Vertex AITerraformAPI gatewaysLiteLLM+1
Advanced