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NVIDIAProfessional2026年更新

NVIDIA-Certified Professional: Generative AI LLMs

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7 Practice Tests

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詳細な解説付きの試験スタイルの問題を体験し、当社の練習教材の品質をご確認ください。

質問 1/150/15 回答済み
1

Your ReAct agent built with NVIDIA NeMo Agent Toolkit is performing poorly on complex multi-step tasks, often choosing wrong tools or getting stuck in loops. What is the most effective optimization strategy?

1 / 15

バンドルに含まれる練習テスト(7個)

NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 1

Practice exam #1 covering Distributed Training & Infrastructure including tensor cores, profiling, and DGX optimization.

60問
120分
Locked

NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 2

Practice exam #2 emphasizing Model Optimization including quantization, pruning, distillation, and TensorRT-LLM.

60問
120分
Locked

NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 3

Practice exam #3 focusing on Data Preparation including cleaning, tokenization, and RAPIDS workflows.

60問
120分
Locked

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.

60問
120分
Locked

NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 5

Practice exam #5 emphasizing Transformer Architecture & Core Concepts including attention mechanisms and sampling strategies.

60問
120分
Locked

NVIDIA Generative AI LLMs Professional (NCP-GENL) - Practice Exam 6

Practice exam #6 covering production deployment, safety guardrails, and performance tuning for LLM applications.

60問
120分
Locked

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.

60問
120分
Locked

Purchase to unlock all 7 practice tests

Why This Certification Matters

検証されるスキル

  • 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個のスキル

キャリアの利点

対象職種

Senior ML EngineerLLM SpecialistAI Solutions ArchitectDeep Learning Engineer+3

給与範囲

$140,000 - $250,000+

LLM engineering roles growing 40%+ annually as enterprises adopt generative AI

積極的に採用している業界

Enterprise AIHealthcare & Life SciencesFinancial ServicesTechnology & SoftwareConsultingResearch & AcademiaAutonomous Systems

試験トピックとドメイン

認定試験は、10つの主要なコンピテンシー領域にわたってあなたの知識を評価します:

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Hard and detailed questions!

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7 full-length practice tests
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