Course Overview

This course is designed to provide both theoretical and practical knowledge of Generative AI and multimodal systems. It covers the principles and techniques behind the generation and transformation of multimodal data such as text, images, audio, and video. Through a combination of interactive units, videos, hands-on labs, and knowledge checks, you will gain a deep understanding of how to work with cutting-edge generative models and AI technologies. By the end of the course, you will be equipped to design, deploy, and optimize generative AI systems, as well as leverage these skills in real-world applications in areas like content creation, AI-driven automation, and advanced machine learning tasks. This course also gives background knowledge that can be useful for those who wish to go further into NVIDIA LLM specialization.

After completing this course of training , you will be able to :

  • Understand the basics of machine learning and AI
  • Work with multimodal data effectively
  • Conduct and analyse experiments
  • Develop and deploy multimodal AI systems
  • Optimize AI performance
  • Apply ethical principles to AI development

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  • 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 and researchers
  • Machine learning engineers
  • Senior researchers
  • Software engineers
  • Solutions architects

Pre-requisites of NCP-GENM course:

Pre-requisites of NCP-GENM course:

Learning objective of the NCP-GENM Certification Training

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

Why choose CloudThat as your training partner for NVIDIA Courses

  • We have well-trained, experienced, and certified Subject matter experts and instructors to conduct these trainings.
  • The course guides students through specific tasks and real-world challenges to help them understand the relevance, power, and usefulness of Microsoft Word.

Course Outline Download Course Outline

  • Basic concepts and terminology
  • Key algorithms and techniques

  • Handling and integrating text, image, and audio data
  • Applications and use cases

  • Designing and conducting experiments
  • Analyzing experimental results

  • Data preprocessing and feature engineering
  • Visualization techniques for multimodal data

  • Python libraries for multimodal AI
  • Integration and deployment of multimodal AI systems

  • Techniques for optimizing AI performance
  • Monitoring and improving system efficiency

  • Ethical considerations in AI development
  • Ensuring fairness and transparency

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Course ID: 24802

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FAQs on NVIDIA-Certified Associate Generative AI Multimodal (NCA-GENM)

NVIDIA offers a range of courses through its Deep Learning Institute (DLI), designed to help individuals and organizations gain skills in cutting-edge technologies like AI, data science, accelerated computing, and more. These courses are available in various formats, including self-paced online training and instructor-led workshops

Yes, NVIDIA does offer some free courses through its Deep Learning Institute (DLI). These include introductory courses on topics like CUDA programming and generative AI. However, many of their more advanced or specialized courses require payment. You can explore their free course offerings from the NVIDIA website. Let me know if you'd like help finding a specific course!

Yes, NVIDIA courses often require specific software and tools, depending on the course topic.

The prior knowledge required for NVIDIA courses depends on the specific course you're interested in. Here are some general guidelines: Beginner-Level Courses: These often require little to no prior knowledge. For example, NVIDIA CUDA Programming Course or generative AI are introductory courses designed for newcomers. For professionals looking to further their expertise, NVIDIA Deep Learning Institute Certification provides advanced specializations. Intermediate and Advanced Courses: These may require familiarity with programming languages like Python or C++, basic knowledge of machine learning or deep learning concepts, and experience with tools like TensorFlow or PyTorch. Specialized Topics: Courses on AI infrastructure, GPU computing, or advanced networking might require a background in IT, data science, or related fields.

Core Concepts: Understand multimodal generative AI, transformers, diffusion models, and prompt engineering. NVIDIA Tools: Learn to use CUDA, Triton, and NeMo for building multimodal applications. Key Topics: Focus on machine learning basics, data visualization, and trustworthy AI principles. Online Courses: Take specialized training via Udemy or NVIDIA's certification page. Practice: Work on projects combining text, images, video, and speech generation. Exam Details: Study the exam blueprint; it's a 60-minute test with 50-60 questions.

Yes, many NVIDIA courses include evaluations or certifications that require payment. For example, some self-paced courses offer certificates of competency, which are available for a fee. However, there are also free courses that do not include evaluations or certifications

After successfully clearing the NCA-GENM assessment, you'll receive a digital badge and an optional certificate that validate your expertise in multimodal generative AI. This certification is valid for two years, and you can renew it by retaking the exam. The certification demonstrates your foundational skills in multimodal AI, including text, image, video, and speech generation. It can enhance your career prospects in roles like AI developer, data scientist, or multimodal AI specialist. Additionally, it opens doors to advanced certifications and specialized projects in the field of generative AI. This course can also be considered a stepping stone to further NVIDIA Machine Learning Certification.

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