What You'll Learn
- Learn how GPUs accelerate AI workloads and master the architecture of Tensor Cores, Streaming Multiprocessors (SMs), NVLink, and MIG for efficient computing.
- Understand the full AI lifecycle: from model development and training to deployment, monitoring, and scaling across enterprise infrastructure.
- Gain hands-on experience using DCGM, NGC, Triton Inference Server, and Helm Charts to deploy and monitor real AI workloads in simulated environments.
- Explore GPU-accelerated storage, RDMA, GPUDirect, and compare networking standards like InfiniBand vs Ethernet for optimal AI performance.
- Work with vGPUs, multi-tenant deployments, DPUs, and the DOCA SDK to support secure, scalable, and software-defined AI infrastructure.
- Prepare to pass the NCA-AIIO exam with a full-length mock test, flashcards, exam tips, and a readiness checklist tailored to NVIDIA’s official blueprint.
Requirements
- Basic knowledge of IT systems (servers, storage, networking, or Linux)
- Familiarity with cloud platforms (AWS, Azure, or GCP) is helpful, but not required
- No prior GPU or AI experience needed—everything is explained from the ground up
- A computer with a modern web browser and internet connection to access labs
- (Optional) A free Google Colab or NVIDIA NGC account for hands-on labs
Who This Course is For
- IT professionals and system administrators managing data center hardware and infrastructure
- DevOps and Cloud Engineers looking to deploy, scale, and monitor GPU-accelerated AI workloads
- Machine Learning Ops (MLOps) teams aiming to bridge the gap between AI models and infrastructure
- AI/ML enthusiasts or beginners seeking a structured entry point into AI infrastructure management
- Students or career switchers preparing for the NVIDIA-Certified Associate: AI Infrastructure and Operations (NCA-AIIO) exam
- Technical teams in enterprise IT, cloud-native operations, or AI engineering roles needing hands-on NVIDIA ecosystem experience
Your Instructor
School of AI
AI Academy
4.4 Instructor Rating
8,562 Reviews
328,933 Students
86 Courses
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