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Cisco 300-640 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Infrastructure Components and Architecture	30%	- Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures - Evaluate power, cooling, and efficiency requirements - Evaluate hybrid and multi-cloud AI integration - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability
Topic 2: AI Infrastructure Deployment and Data Management	30%	- Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Deploy and manage AI infrastructure with orchestration tools - Integrate AI frameworks and applications with Cisco infrastructure - Implement data management and lifecycle for AI workloads
Topic 3: AI Infrastructure Operations and Troubleshooting	20%	- Optimize performance, security, and reliability - Manage health, logs, and events - Troubleshoot network, compute, storage, and orchestration issues - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Implement performance benchmarking and validation
Topic 4: AI Infrastructure Fundamentals	20%	- Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Describe AI and machine learning concepts - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Explain Cisco AI infrastructure solutions and portfolio - Describe AI use cases in data center environments

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q26-Q31):

NEW QUESTION # 26
Which components are part of the HyperFabric AI solution?

A. Cisco UCS servers with NVIDIA GPUs, switches, optional VAST Data Storage and cloud- managed networking
B. combination of Cisco networking hardware and software-defined storage designed for AI scalability
C. Cisco UCS servers combined with high-speed networking switches and third-party storage
D. integrated compute and networking hardware optimized for AI workloads, with optional cloud management

Answer: A

Explanation:
HyperFabric AI combines Cisco UCS servers with NVIDIA GPUs, Cisco Nexus 6000 Series switches, optional VAST Data storage, and cloud-managed networking to provide an integrated AI infrastructure solution for training and inference workloads.

NEW QUESTION # 27
A nationwide grocery chain has deployed Unified Edge to all its locations. Each store has 10 or more surveillance cameras that write approximately 1 Gb per hour. The surveillance retention policy requires maintaining 2 weeks of recording per camera. Which type of cost-effective centralized storage solution must be evaluated with Unified Edge devices to adhere to this policy?

A. Infiniband shared storage
B. IP-based shared storage
C. local storage
D. Fibre Channel shared storage

Answer: B

Explanation:
Unified Edge deployments that need centralized, cost-effective retention for large surveillance data volumes should evaluate IP-based shared storage. It provides scalable network-accessible capacity for multiple edge devices without requiring specialized Fibre Channel or InfiniBand infrastructure, making it appropriate for distributed video retention workloads.

NEW QUESTION # 28
A Cisco AI infrastructure requires fast convergence after a spine switch failure. Which routing design principle best supports this objective?

A. Single-path forwarding
B. Static route redistribution
C. Layer 2 loop dependency
D. Equal-cost multipath routing

Answer: D

Explanation:
ECMP provides multiple active forwarding paths and enables rapid failover when a path becomes unavailable. AI environments benefit from resilient high-bandwidth forwarding. Static redistribution slows operational flexibility, while single-path forwarding and Layer 2 dependency reduce scalability and convergence efficiency.

NEW QUESTION # 29
A Cisco AI cluster requires segmentation between multiple research teams sharing the same physical infrastructure. Which solution provides scalable tenant isolation?

A. Static NAT
B. VXLAN overlays
C. VLAN-only design
D. Hub-and-spoke WAN

Answer: B

Explanation:
VXLAN overlays provide scalable multi-tenant segmentation using large VNI spaces beyond traditional VLAN limitations. AI infrastructures often support many isolated environments simultaneously. VLAN-only designs have scalability constraints, while WAN topologies and NAT do not provide modern data center tenant segmentation.

NEW QUESTION # 30
How does RAG enhance the capabilities of LLMs?

A. by removing the data preparation and cleaning step
B. by retaining the LLM by altering its core parameters
C. by providing access to proprietary data
D. by removing inherent biases from LLM outputs

Answer: C

Explanation:
RAG enhances LLMs by retrieving relevant external or proprietary information at generation time and using that context to produce more accurate, current, and domain-specific responses without changing the model's core parameters.

NEW QUESTION # 31
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