NVIDIA Generative AI LLM Professional
NCP-GENL cert track
- Level
- Professional
- Time
- ~27 hr
- Modules
- 7
- Status
- Planned
Prep scope
Production LLM systems: RAG pipelines at scale, model parallelism, inference optimization, and deployment patterns. Completes the NVIDIA LLM instructor track.
Cert track · NVIDIA self-paced
The NVIDIA self-paced courses in this cert prep path. Free courses do not require Inception codes; paid courses redeem one code each.
- S-FX-33Substitute
Domain-Adaptive Pre-Training: Tailoring LLMs for Specialized Applications
4h - S-FX-24Substitute
The Art of Compressing LLMs: Pruning, Distillation, and Quantization
8h - S-FX-18Substitute
Sizing LLM Inference Systems
3h - S-FX-15
Building RAG Agents with LLMs
8h - S-FX-19
Introduction to Deploying RAG Pipelines for Production at Scale
4h
Cert track · BakedIn parallel courses
BakedIn cert-prep guides being authored against the same exam blueprint. Validated by Glen passing the cert from the BakedIn content.
BakedIn LLM Domain Adaptation + Compression
Pairs to S-FX-33 + S-FX-24 (substitutes for Adding New Knowledge workshop). DAPT, SFT, DPO, quantization, pruning, distillation.
BakedIn LLM Inference at Scale
Pairs to S-FX-18 (substitute for Deploying & Optimizing Inference workshop). Inference economics, model serving, latency optimization. Backed by Bedrock-routed per-task model selection.
BakedIn RAG Foundations
Shared with NCP-AAI track.
BakedIn RAG Production
Shared with NCP-AAI track.
How this prep is built
Each cert prep guide on this site is authored via the same BakedIn content pipeline that produces the Getting Ready for AI pathway: ingestion of vendor source material, structured synthesis with citations, generated practice items, and evaluations against the exam blueprint.
The methodology was proven by hand on four earlier certs (CISSP, CISM, CISA, CRISC). AI learning engineering is what scales it across the guides currently in flight.
Guide content is still being authored. This is a roadmap page, not a finished product.