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Exam Information
Official specifications published by NVIDIA
Exam Format
60 min
50
70%
Associate
Registration
$125 USD
Online Proctored or online proctoring
English
Validity
2 years
Retake the current exam; Pass a higher-level NVIDIA certification exam
NCA-GENL Exam Topics and Domains
NCA-GENL is organized into 5 weighted domains. Expect to work with NVIDIA AI Enterprise, NVIDIA NeMo, MLflow, NVIDIA Base Command, and more.
1
Core Machine Learning and AI Knowledge
30%
Machine Learning Fundamentals
Neural Network BasicsDeep Learning Concepts
- Understand fundamental machine learning and neural network concepts
- Explain the mathematical foundations of deep learning
- Identify appropriate architectures for different tasks
Transformer Architecture and LLMs
Transformer FundamentalsLarge Language Model Architectures
- Explain transformer architecture components and their functions
- Compare different LLM architectures and their use cases
- Understand how self-supervision improves transformer models
Generative AI Concepts
Generative Model TypesRetrieval-Augmented Generation (RAG)
- Understand different generative AI approaches
- Implement RAG systems for enhanced accuracy
- Evaluate generative model performance
2
Software Development
24%
LLM Integration and Deployment
Model Deployment with NVIDIA ToolsPython Integration for LLMs
- Deploy LLMs using NVIDIA infrastructure
- Integrate LLMs into production applications
- Optimize performance and scalability
Prompt Engineering
Prompt Design TechniquesAdvanced Prompting Strategies
- Master various prompting techniques
- Design prompts for specific use cases
- Evaluate prompt effectiveness
LLM Application Architecture
Scalable Architecture Design
- Design production-ready LLM architectures
- Implement scalable deployment patterns
- Optimize resource utilization
3
Experimentation
22%
Model Customization and Fine-tuning
Fine-tuning StrategiesTraining Configuration
- Implement various fine-tuning techniques
- Optimize training configurations
- Evaluate model improvements
Model Evaluation and Testing
Evaluation MetricsA/B Testing and Experimentation
- Design and conduct model experiments
- Analyze and interpret results
- Implement continuous improvement processes
4
Data Analysis and Visualization
14%
Data Preprocessing for LLMs
Text Data PreparationGPU-Accelerated Data Processing
- Prepare and preprocess data for LLMs
- Leverage GPU acceleration for data tasks
- Build efficient data pipelines
Performance Analysis and Visualization
Model Performance Visualization
- Visualize model behavior and performance
- Create monitoring dashboards
- Interpret complex data patterns
5
Trustworthy AI
10%
AI Safety and Ethics
Responsible AI PracticesSecurity and Guardrails
- Implement responsible AI practices
- Deploy safety guardrails for LLMs
- Ensure ethical AI deployment
Model Governance
Compliance and Auditing
- Establish model governance frameworks
- Ensure compliance with regulations
- Maintain proper documentation
How do I earn this certification?
Passing NCA-GENL earns the NVIDIA Certified Associate in Generative AI and LLMs certification. It sits in the Generative AI and Large Language Models track.
Current Level Exams
- NCA-MGenAI - Multimodal Generative AI
- NCA-AIIO - AI Infrastructure and Operations
Next Level Options
- NCP-AIO - NVIDIA Certified Professional - AI Operations
- NCP-AII - NVIDIA Certified Professional - AI Infrastructure
Alternative Paths
- NCA-AIIO - AI Infrastructure and OperationsFoundation for managing AI infrastructure
- NCA-MGenAI - Multimodal Generative AI Extends to text, image, and audio modalities
Practice with Precision
The PlanetCert Simulator mirrors the real exam environment with authentic questions and timed pressure.
How to study for this exam?
Use the official PlanetCert Practice Test alongside the study plan below to prepare efficiently for NCA-GENL.
What's changed on this exam?
Current Status
- ACTIVE
- Last content update: 2024-09-15
- Announcement date: 2023-06-01
Updates
- NVIDIA NeMo Framework 2.0 Updated content on model customization and deployment • Release date: 2024-09-01
- NVIDIA Triton Inference Server 24.11 New features for LLM-specific optimizations • Release date: 2024-11-01
- RAPIDS 24.10 Enhanced GPU-accelerated data processing capabilities • Release date: 2024-10-01
- LangChain 0.3.0 New integration patterns with NVIDIA tools • Release date: 2024-11-15
Who should take this exam?
This exam is typically taken by AI Engineers and Data Scientists.
- Basic understanding of generative AI and large language models
- Familiarity with Python programming
- Understanding of Linux command line
- Basic knowledge of machine learning concepts