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Cisco 300-640 Exam Syllabus Topics:

Section	Objectives
Topic 1: Data Center Networking for AI Workloads	- High-performance fabric design 1. Leaf-spine architecture in AI environments 2. Low-latency switching and routing considerations - Cisco Data Center networking technologies 1. Cisco ACI integration concepts 2. Cisco Nexus platform concepts
Topic 2: AI Infrastructure Deployment and Operations	- Operations and lifecycle management 1. Monitoring and observability 2. Performance tuning and optimization - Deployment models 1. On-premises AI clusters 2. Hybrid AI infrastructure integration
Topic 3: Compute and Storage for AI Infrastructure	- Storage systems 1. Distributed storage concepts 2. High-throughput storage for AI training data - Compute architecture 1. HPC-style scaling considerations 2. GPU-based compute nodes
Topic 4: Data Center AI Infrastructure Fundamentals	- AI/ML workload requirements in data centers 1. Data pipeline and workload characteristics 2. Compute, GPU, and acceleration concepts
Topic 5: Security and Governance in AI Data Centers	- Infrastructure security 1. Network segmentation and policy enforcement 2. Secure access to AI workloads

Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:

Question #1

Which network design approach should be used to build a high-performance, nonblocking AI/ML data center fabric that supports 64 fully equipped UCS C885A nodes and provides the lowest possible latency and lossless Ethernet?

A. flat Layer 2
B. leaf-spine
C. traditional three-tier
D. rail optimized

Reveal Solution Discussion 0

Correct Answer: D 🗳️