Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
4 Hour(s) 40 Minute(s)
Language
English
Taught by
Ashish Prajapati
Rating
Course Overview
Your Guide to Understanding NVIDIA-Powered AI Infrastructure - From Fundamentals to Certification Success
Embark on a transformative journey into the world of AI infrastructure with this comprehensive course designed to prepare you for the NVIDIA Certified Associate: AI Infrastructure and Operations (NCA-AIIO) certification. Whether you're an IT professional, system administrator, or DevOps engineer, this course equips you with the foundational knowledge and practical skills needed to manage and optimize AI workloads in data center environments.
What You'll Learn:
AI Fundamentals: Understand the core concepts of Artificial Intelligence, Machine Learning, and Deep Learning, and their applications in modern computing.
NVIDIA Hardware & Software: Gain proficiency in NVIDIA's GPU architectures, including A100, H100, and B200, and explore essential software tools like CUDA, DCGM, and NGC Catalog.
Infrastructure Design: Learn about data center components, networking technologies such as NVLink and InfiniBand, and how to design scalable AI infrastructure.
AI Operations: Master the deployment, monitoring, and optimization of AI workloads in a enterprise data center, utilizing tools like DCGM, Slurm and Kubernetes.
Exam Preparation: Prepare thoroughly for the NCA-AIIO exam with detailed study guides, practice questions, and real-world scenarios. Gain a clear understanding of the exam objectives, learn tips to maximize your performance, and build confidence to pass the certification on your first attempt, validating your expertise in AI infrastructure operations
Course Content
- 6 section(s)
- 72 lecture(s)
- Section 1 Introduction
- Section 2 Certification Details
- Section 3 Module 1 - Fundamentals
- Section 4 Module 2 - Inside an AI centric Data Center
- Section 5 Module 3 - NVIDIA Technology Stack
- Section 6 Module 4 - AI Workflows
What You’ll Learn
- Comprehend GPU Architecture and Use Cases - Learn about GPU architecture and its role in accelerating AI workloads across various industries.
- Prepare for NVIDIA NCA-AIIO Certification - Gain the knowledge and skills needed to successfully pass the NVIDIA AI Infrastructure Operations Associate exam.
- Navigate NVIDIA Software Suite – Learn CUDA, GPU cores, DGX, NVLink, InfiniBand, DCGM, GPUDirect, and key tools for AI data center operations.
- Comprehend GPU Architecture and Use Cases Learn about GPU architecture and its role in accelerating AI workloads across various industries.
Skills covered in this course
Reviews
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JJeevan Chenna
The way of explanation is very good and helps me understand the basics as a beginner. Please continue with this style — I highly recommend it. I’m also expecting an NCP-AII/AIO/AIN certifications for senior-level courses soon.
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BBalraj Dahiya
Excellent course to deep dive into NVIDIA AI Infrastructure and Operations. It provides a clear, well-structured learning path for understanding how to design, deploy, and manage AI-optimized infrastructure using NVIDIA’s AI ecosystem. Each complex topic explained in simplest way with practical example. I would highly recommend this course to anyone who is learning and preparing for NVIDIA AI Infrastructure Operations Associate exam.
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UUmair Sajid
it is a good introductory course for Nvidia AI infra. however it was missing some key technical details and hands-on
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VVinitha S
The NVIDIA-Powered AI Infrastructure course was an outstanding learning experience and a perfect preparation pathway for the NVIDIA AI Infrastructure & Operations Associate certification. The content was practical, well-paced, and clearly designed for a solid grasp of the AI architectural fundamentals. I especially appreciated how the course breaks down complex concepts into digestible modules. The content is extremely relevant for anyone planning to deploy or manage AI workloads at scale and provides a solid understanding of how to approach building reliable, high-performance AI infrastructure in production environments.
