Descriptions
Course NVIDIA Certified Professional AI Networking (NCP-AIN), Note: This course contains the use of artificial intelligence Voice (AI Voice). This course does not include Hands On sessions. This fast-track, fundamentals-first training is a concept-driven, architecture-focused course created for professionals preparing for the NVIDIA Certified Professional AI Networking (NCP-AIN) certification or anyone who wants a deep, structured understanding of NVIDIA AI networking ecosystems without relying on hands-on labs. The course includes two downloadable eBooks and focuses on clearing the certification exam, understanding deep concepts, and achieving full fundamentals clarity.
The curriculum walks through the entire NVIDIA AI networking landscape: AI data center design and optimization; Ethernet-based Spectrum‑X fabrics and NVIDIA InfiniBand concepts; rail‑optimized and scalable network topologies; GPU-to-GPU communication fundamentals; DPUs, BlueField, SuperNICs and telemetry; QoS, ECN, PFC and congestion management; Kubernetes integration with RDMA and GPUDirect; observability and diagnostic tools such as NetQ, UFM and WJH; automation with NVUE, ZTP and Ansible; and troubleshooting and performance tuning. The course emphasizes fundamentals-first learning (no lab dependency), clear architectural explanations with flows and diagrams, certification alignment without exam cramming, and an enterprise-grade perspective—preparing learners to reason about AI networking designs, communicate with architects and vendors, and tackle real-world AI data center challenges with confidence.
What you’ll learn
- Understand NVIDIA AI data center networking architecture and how GPUs, DPUs, switches, and storage work together for AI workloads.
- Explain AI factory design principles and rail-optimized network topologies for scalable, high-performance NVIDIA environments.
- Differentiate NVIDIA Spectrum-X Ethernet and InfiniBand networking concepts for AI training and inference workloads.
- Understand GPU-to-GPU communication fundamentals and how network design impacts latency, throughput, and AI performance.
- Learn core concepts of QoS, congestion control, telemetry, and observability in NVIDIA AI networking environments.
- Understand how Kubernetes integrates with NVIDIA AI networking, including RDMA, InfiniBand, and GPU resource awareness.
- Develop architectural reasoning to analyze AI network performance, scalability, and reliability challenges.
- Prepare for NVIDIA NCP-AIN certification with strong conceptual clarity and design-focused understanding.
Who this course is for
- Network engineers who want to transition into AI data center and GPU networking roles
- Data center and infrastructure architects designing or supporting AI and GPU-based environments
- Platform and cloud engineers working with AI workloads and high-performance networking
- Kubernetes professionals who want to understand AI networking integration concepts
- AI infrastructure, MLOps, and platform teams seeking architecture-level clarity
- Technical leads and decision-makers involved in AI data center design and planning
- Professionals preparing for the NVIDIA Certified Professional AI Networking (NCP-AIN) certification
- Engineers who prefer to understand design principles, trade-offs, and architectures before execution
Specificatoin of Course NVIDIA Certified Professional AI Networking (NCP-AIN)
- Publisher : Udemy
- Teacher : QuickTechie HadoopExam
- Language : English
- Level : All Levels
- Duration : 11 hours and 3 minutes
Content of Course NVIDIA Certified Professional AI Networking (NCP-AIN)
Requirements
- This course is designed to build understanding from core networking and AI infrastructure fundamentals.
- Basic understanding of computer networking concepts (IP, routing, switching)
- General familiarity with data center or cloud infrastructure concepts
- Awareness of AI, GPU computing, or machine learning workflows (helpful but not required)
- Interest in AI infrastructure, data center design, or high-performance networking
Pictures
Sample Clip
Installation Guide
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Quality: 1080p
Download Links
Password file(s): www.downloadly.ir
File size
1.94 GB
