NVIDIA-Certified Associate: Generative AI Multimodal (NCA-GENM)

The NCA Generative AI Multimodal certification is an entry-level credential that validates the foundational skills needed to design, implement, and manage AI systems that synthesize and interpret data across text, image, and audio modalities.


Students should have a basic understanding of generative AI

Recommended training for this certification

  • Generative AI Explained (self-paced course, 2 hours, free)
  • Getting Started With Deep Learning (self-paced course, 8 hours) or Fundamentals of Deep Learning (instructor-led workshop, 8 hours)
  • Fundamentals of Accelerated Data Science (instructor-led workshop, 8 hours)
  • Get Started With Highly Accurate Custom ASR for Speech AI (self-paced course, 3 hours)
  • Building Conversational AI Applications​ (instructor-led workshop, 8 hours)
  • Introduction to Transformer-Based Natural Language Processing (self-paced course, 6 hours)
  • Generative AI With Diffusion Models​ (self-paced course, 8 hours) or Generative AI With Diffusion Models (instructor-led workshop, 8 hours)
  • Deploying a Model for Inference at Production Scale (self-paced course, 4 hours)
  • Efficient Large Language Model (LLM) Customization (instructor-led workshop, 8 hours)
  • Prompt Engineering With LLaMA-2 (self-paced course, 3 hours)
  • Rapid Application Development Using Large Language Models (LLMs) (instructor-led workshop, 8 hours)
  • Computer Vision for Industrial Inspection (instructor-led workshop, 8 hours)
  • Applications of AI for Anomaly Detection (instructor-led workshop, 8 hours)
  • Applications of AI for Predictive Maintenance (instructor-led workshop, 8 hours)


Certification Exam Details

  • Duration: One hour
  • Price: $135
  • Certification level: Associate
  • Subject: Multimodal generative AI
  • Number of questions: 50
  • Language: English

Candidate audiences:

  • AI DevOps engineers
  • AI strategists
  • Applied data research engineers
  • Applied data scientists
  • Applied deep learning research scientists
  • Cloud solution architects
  • Data scientists
  • Deep learning performance engineers
  • Generative AI specialists
  • Large language model (LLM) specialists/researchers
  • Machine learning engineers
  • Senior researchers
  • Software engineers
  • Solutions architects

Topics covered in the exam include:

  • Core machine learning/AI knowledge
  • Data analysis and visualization
  • Experimentation
  • Multimodal data
  • Performance optimization
  • Software development and engineering
  • Trustworthy AI


This certification is valid for two years from issuance.

Recertification may be achieved by retaking the exam.