NVIDIA· Professional

NVIDIA-Certified Professional: Generative AI LLMs

NCP-GENL

The NCP-GENL exam tests whether you can train, fine-tune, optimize and deploy large language models on NVIDIA GPUs, with evaluation and production reliability in scope. The preporato.com prep for this NVIDIA generative AI LLM certification pairs timed practice exams, every question explained, with hands-on GPU labs.

420+

Questions

7

Pruebas de Práctica

22

Hands-on labs

Lifetime

Updates

Qué Incluye

Practice

7 exam-realistic practice tests

420+ questions
Practice exam · NCP-GENLQ 1 / 65
Correct · explanation

Hands-on

Labs· 22

# vLLM · 10 concurrent
$ asyncio.gather(…)
wall time ....... 3.8s
throughput ...... 1,842 tok/s
GPU Pro
intermediate45m

Deploy & Serve LLMs in Production (Jupyter)

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# lora · r=16 · alpha=32
$ trainer.train()
trainable ....... 0.8%
eval_loss ....... 1.24
perplexity ...... 3.45
GPU Pro
intermediate45m

Fine-Tune an LLM with LoRA and QLoRA (Jupyter)

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naiveaddtiledautograd
GPU Pro
advanced45m

CUDA Programming Fundamentals

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fp16int8nf4
GPU Pro
intermediate40m

Quantize & Optimize LLMs with bitsandbytes

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# torch.profiler · top ops
$ table(sort=cuda_time)
gemm ........ 41%
memcpy ...... 22%
softmax ..... 9%
GPU Pro
intermediate35m

Profile PyTorch Training with the Built-in Profiler

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GPU Pro
advanced40m

Advanced RAG: Hybrid Search + Cross-Encoder Reranking

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GPU Pro
advanced45m

Continued Pre-Training: Adapt a Pretrained LM to a New Domain

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CPUDALI
GPU Pro
intermediate30m

NVIDIA DALI: GPU-Accelerated Data Pipelines

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# dedup + tokenize
$ filter_lang("en")
raw ............ 52k → 18k
tokenizer ...... BPE 32k
train_ready .... 16,420
GPU Pro
intermediate45m

Data Preparation for LLM Training

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GPU Pro
advanced55m

RLHF & DPO Alignment

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GPU Pro
intermediate45m

Evaluation & Benchmarking LLMs

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GPU Pro
intermediate40m

Inference Serving Patterns: Dynamic Batching, Throughput, and the Triton Mental Model

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GPU Pro
intermediate35m

Nsight Systems Profiling: Finding the Bottleneck That Costs You 40% of Your GPU

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fp32fp16bf16
GPU Pro
intermediate40m

Batch Size & Precision Sweep: Finding Your Sweet Spot

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Retrieval-Augmented Generation (RAG) Pipeline with Local Models labGPU Pro
intermediate45m

Retrieval-Augmented Generation (RAG) Pipeline with Local Models

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Reproducible Training: The Flags, The Cost, The Artifacts labGPU Pro
intermediate40m

Reproducible Training: The Flags, The Cost, The Artifacts

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Fine-Tune Stable Diffusion with LoRA: Custom Text-to-Image labGPU Pro
intermediate45m

Fine-Tune Stable Diffusion with LoRA: Custom Text-to-Image

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Synthetic Data Generation for Model Training labGPU Pro
intermediate40m

Synthetic Data Generation for Model Training

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Train a Small Language Model from Scratch labGPU Pro
advanced55m

Train a Small Language Model from Scratch

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Build a Transformer from Scratch: Attention, Masking & LayerNorm labGPU Pro
advanced50m

Build a Transformer from Scratch: Attention, Masking & LayerNorm

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vLLM Production Serving: PagedAttention, Continuous Batching, Prefix Caching labGPU Pro
advanced55m

vLLM Production Serving: PagedAttention, Continuous Batching, Prefix Caching

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Build NeMo Guardrails for an AI Agent: Jailbreak & Topical Rails labHosted Pro
intermediate35m

Build NeMo Guardrails for an AI Agent: Jailbreak & Topical Rails

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