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 hHighest 2026 demand — builds and operates production AI features
PythonFastAPILangChainLangGraphLlamaIndexpgvector+7
Anchor track
R2 · GenAI / LLM Engineer
160 hHighest-paid specialisation — adapts, serves and evaluates models
PyTorchHugging Face TransformersDatasetsPEFTTRLbitsandbytes+5
R3 · MLOps / LLMOps Engineer
160 h9.8× posting growth — owns the path to production
DockerKubernetesHelmMLflowDVCAirflow+5
R4 · Data Scientist
160 hStrongest official growth signal — BLS +34% to 2034
PythonSQLscikit-learnXGBooststatsmodelsSHAP+4
R5 · Data & RAG Engineer
160 hThe retrieval data layer every AI system depends on
PythonSQLAirflowdbtUnstructuredpgvector+4
R6 · AI Solutions Architect
160 hAdvanced track — designs systems that hold up commercially and legally
AWS BedrockAzure AIGoogle Vertex AITerraformAPI gatewaysLiteLLM+1
Advanced