NVIDIA AI-LLM Devs Certification Path

1. NVIDIA-Certified Associate: Generative AI LLMs (NCA-GENL)

• cost:$125 (~ €100)
• duration: 90 minutes
• Question: 60
• validity: 2 Years
• Exam: https://www.certiverse.com/#/dashboard
• Udemy: https://thoughtworks.udemy.com/course/nvidia-nca-genl/learn
• Syllabus: https://nvdam.widen.net/s/rpdddpdgtc/nvt-certification-exam-study-guide-gen-ai-llm-3262644-r7-web

Why

• Validate knowledge of generative AI and LLMs
• Help stand out in the job market
• Demonstrate commitment to AI expertise

Learning Resources

Generative AI for Everyone

• Week 1: Introduction to Generative AI
• Week 2: Generative AI Projects
• Week 3: Generative AI in Business and Society

Random

• How to become a NVIDIA-Certified Associate: Generative AI LLMs (NCA-GENL)
• HuggingFace Course
• Nvida GenAI Learning Path

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2. Nvidia-Certified Professional: Agent-Based AI (NCP-AGENT)

• cost: $250 (~ €200)
• duration: 120 minutes
• Question: 80
• validity: 2 Years
• Exam: https://www.certiverse.com/#/dashboard
• Udemy: https://thoughtworks.udemy.com/course/nvidia-ncp-agent/learn

Agentic AI

• Module 1: Introduction to Agentic Workflows
• Module 2: Reflection Design Pattern
• Module 3: Tool use
• Module 4: Practical Tips for Building Agentic AI
• Module 5: Patterns for Highly Autonomous Agents

Coverage:

Topic Area	Weight	What You’re Expected to Know
Agent Architecture and Design	15%	Multi-agent systems, agent workflows, orchestration patterns, tool use, communication protocols, reasoning loops, autonomous vs semi-autonomous agents
Agent Development	15%	Building agents with frameworks, integrating APIs/tools, prompt engineering, RAG pipelines, function calling, workflow chaining
Evaluation and Tuning	13%	Benchmarking agents, evaluation metrics, hallucination reduction, latency optimization, cost/performance tradeoffs, prompt tuning
Deployment and Scaling	13%	Containerization, inference scaling, distributed systems, GPU utilization, Kubernetes, production deployment strategies
Cognition, Planning, and Memory	10%	Chain-of-thought, planning algorithms, memory systems, context windows, episodic vs semantic memory, reasoning strategies
Knowledge Integration and Data Handling	10%	Vector databases, embeddings, RAG, structured/unstructured data pipelines, retrieval optimization
NVIDIA Platform Implementation	7%	NVIDIA AI stack, CUDA, TensorRT, NIMs, NeMo, Triton Inference Server, DGX ecosystem
Run, Monitor, and Maintain	5%	Observability, logging, tracing, telemetry, drift detection, monitoring inference systems
Safety, Ethics, and Compliance	5%	AI governance, bias mitigation, security, privacy, guardrails, compliance principles
Human-AI Interaction and Oversight	5%	Human-in-the-loop systems, feedback mechanisms, approval workflows, UX for AI agents