NVIDIA-Certified Associate: Generative AI Multimodal exam guide

Who it's for

Developers and data scientists with a basic understanding of generative AI who work with image, audio or vision-language models.

What the exam covers

Eligibility & prerequisites

Required: None.

Recommended: Basic understanding of generative AI; NVIDIA recommends Fundamentals of Deep Learning and Building AI Agents With Multimodal Models.

Keeping it active

Valid 2 years from issuance. Recertify by retaking the current version of the exam before it expires.

Skills & careers

Where it fits in your path

Planning a degree too? See how this cert earns college credit in the College Credit Navigator.

Build my study plan

1. Week 1: Deep learning refresher: CNNs, transformers, embeddings and contrastive learning (CLIP-style).
2. Week 2: Multimodal generation: diffusion models, vision-language models, speech models; data preparation for each modality.
3. Week 3: NVIDIA's Building AI Agents With Multimodal Models course; build a small image-plus-text pipeline.
4. Week 4: Experimentation, optimization (quantization, batching, TensorRT concepts), trustworthy AI; practice questions and review.

Exam-day tips

• Experimentation is the largest domain at 25%; know how to compare models and read evaluation results.
• Be clear on how modalities are fused (early vs late fusion, shared embedding spaces).
• Expect questions on NVIDIA tooling for inference performance; know what TensorRT and Triton do.
• Trustworthy AI is only 5% but watermarking, deepfakes and consent for generated media are likely topics.

Key terms for this exam

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Frequently asked questions