NVIDIA-Certified Professional: Generative AI LLMs
Pass your certification on the first attempt with exam-realistic practice tests and detailed explanations
What's Included in Your Practice Bundle
7 Practice Tests
Full-length exam simulations
420+
Practice Questions
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120 min
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Try Before You Buy - Free Practice Questions
Experience exam-style questions with detailed explanations and see the quality of our practice materials.
When preparing a large web-scraped dataset for LLM pre-training, which quality filtering step is most critical to prevent memorization and improve generalization?
Practice Tests Included in the Bundle (7)
NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 1
Practice exam #1 covering Distributed Training & Infrastructure including tensor cores, profiling, and DGX optimization.
NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 2
Practice exam #2 emphasizing Model Optimization including quantization, pruning, distillation, and TensorRT-LLM.
NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 3
Practice exam #3 focusing on Data Preparation including cleaning, tokenization, and RAPIDS workflows.
NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 4
Practice exam #4 covering Prompt Engineering & Advanced Techniques including few-shot, CoT, ReAct, and constrained decoding.
NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 5
Practice exam #5 emphasizing Transformer Architecture & Core Concepts including attention mechanisms and sampling strategies.
NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 6
Practice exam #6 covering production deployment, safety guardrails, and performance tuning for LLM applications.
NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 7
Comprehensive practice exam #7 covering all NCP-GENL domains with scenario-based questions and real-world LLM deployment challenges.
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Why This Certification Matters
Skills You'll Validate
- Designing and training large language models
- Advanced prompt engineering (CoT, zero/one/few-shot learning)
- Fine-tuning techniques (Full, PEFT, LoRA, QLoRA)
- Distributed training and multi-GPU optimization
- Model quantization, pruning, and distillation
- TensorRT-LLM optimization for inference
- +6 more skills
Career Benefits
Target Roles
Salary Range
$140,000 - $250,000+
LLM engineering roles growing 40%+ annually as enterprises adopt generative AI
Industries Actively Hiring
Exam Topics & Domains
The certification exam evaluates your knowledge across 10 key competency areas:
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