Course Overview

We start the journey with an Introduction to AI where we cover AI basic concepts and principles. Then, we delve into data center and cloud infrastructure followed by AI operations. This certification is an entry-level credential that validates the foundational concepts of AI computing related to infrastructure and operations. The exam is online and proctored remotely, includes 50 questions, and has a 60-minute time limit. This is one of the many NVIDIA online courses available.

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

  • Create and configure resources
  • Programmatically analyse data in forms
  • Create a template-based custom model
  • Configure model endpoints for document types
  • Extract key value pairs

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Who should Attend?

  • • IT Professionals and managers
  • • System and Network Administrators and engineers
  • • DevOps Engineers
  • • Datacenter professionals
  • • Business-line owners
  • • Data center technicians
  • • Delivery and professional services engineers
  • • Sales representatives
  • • Systems administration staff
  • • Solution architects
  • • System architects

Pre-requisites of NCA-AIIO course:

    To enrol in this course, it is recommended to have:<\ul>
  • Basic understanding of data center infrastructure<\li>

Learning objective of the NCA-AIIO Certification Training

  • Express how AI is transforming society.
  • Explain terminology and concepts related to AI.
  • Describe the evolution of GPU computing and its contribution to the AI revolution.
  • Evaluate the NVIDIA hardware and software solutions for AI.
  • Identify the data center infrastructure building blocks and their role in building an AI data center.
  • Recall AI in the data center operation tasks. This knowledge is crucial for the NVIDIA AI Certification.

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

  • AI use cases across different industries
  • The evolution of AI into machine learning, deep learning, and Generative AI, each phase unlocking new capabilities.
  • The emergence of generative AI applications, producing content like music, images, and videos.
  • How GPUs revolutionized AI?
  • The importance of a suitable software stack ensuring optimal performance and efficiency.
  • The environments where AI workloads run - data centers or the cloud. 

  • Compute platforms, networking, and storage for AI.
  • How energy efficient computing practices helps data centers lower their carbon footprint and energy use.
  • How recommended design documents called reference architectures (RAs), can be used as a foundation for building best-of-breed designs. 
  • Moving from an on-prem data center to cloud based solutions that offer a flexible and accessible alternative.

  • Infrastructure management and monitoring
  • Cluster orchestration and job scheduling 

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Course ID: 24763

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FAQs on AI Infrastructure and Operations Fundamentals (NCA-AIIO)

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, introductory courses on CUDA programming or generative AI are designed for newcomers. • 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.

Enroll in Relevant Training: • Take the AI Infrastructure and Operations Fundamentals self-paced course offered by NVIDIA. It's designed to provide foundational knowledge and is highly recommended for this certification

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 assessment for the NVIDIA Certified Associate - AI Infrastructure and Operations (NCA-AIIO) course, you will receive: 1. Digital Badge: A verified digital badge that you can showcase on platforms like LinkedIn or your resume to highlight your certification. 2. Certificate: An optional certificate indicating your achievement and certification level. 3. Recognition: Validation of your foundational knowledge in AI infrastructure and operations, which can enhance your professional credibility. 4. Career Opportunities: This NVIDIA AI certification can open doors to roles in IT, AI infrastructure, and operations, as it demonstrates your expertise in NVIDIA technologies.

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