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300-640 Latest Exam Practice, 300-640 Certification Questions, New 300-640 Braindumps Pdf, 300-640 Valid Exam Guide, Dumps 300-640 Reviews

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Cisco 300-640 Exam Syllabus Topics:

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

>> 300-640 Latest Exam Practice <<

First-hand Cisco 300-640 Latest Exam Practice: Implementing Cisco Data Center AI Infrastructure & 300-640 Certification Questions

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Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q30-Q35):

NEW QUESTION # 30
What is a primary behavior that occurs during the model training stage of the AI lifecycle?

  • A. adjusting internal weights and biases
  • B. establishing success criteria
  • C. embedding the model into systems with APIs
  • D. detecting model drift

Answer: A

Explanation:
During model training, the model learns from training data by iteratively adjusting its internal weights and biases to reduce prediction error and improve performance against the defined objective function.


NEW QUESTION # 31
A server administrator must monitor the performance and utilization of GPUs in Cisco UCS servers running AI workloads. Which two metrics must be used in Cisco Intersight to accomplish these goals? (Choose two.)

  • A. GPU Utilization
  • B. GPU Performance
  • C. System CPU Utilization
  • D. Explorer
  • E. Monitor

Answer: A,B

Explanation:
Cisco Intersight provides GPU-focused telemetry for UCS servers, including utilization and performance metrics. These measurements allow the administrator to monitor how heavily the GPUs are being used and whether the AI workload is receiving the expected GPU performance.


NEW QUESTION # 32
A national law firm is deploying a RAG solution for their legal research team to more efficiently use their 50 TB of confidential data and documents when preparing new contracts and briefs.
They decided on a UCS X-Series chassis equipped with four GPUs and six X210c servers. Which storage solution fits this deployment?

  • A. local storage in a RAID 5 configuration
  • B. tape storage
  • C. IP-based storage array
  • D. local storage in a JBOD configuration

Answer: C

Explanation:
A RAG deployment with 50 TB of confidential documents requires scalable shared storage that can be accessed by multiple UCS X210c servers. An IP-based storage array provides centralized capacity, shared access, and operational simplicity for storing and retrieving large datasets used by the RAG pipeline.


NEW QUESTION # 33
To support growing AI workload requirements, a regional medical practice is adding new X9516 X-Fabric module, UCS PCI Mezz cards, and UCS X580p PCIe nodes to their existing X-Series chassis. Which two administrative actions must be taken before the X-Fabric module is added to the chassis? (Choose two.)

  • A. Install UCS PCI Mezzanine cards in X-Series blades.
  • B. Power down all IFMs in the chassis.
  • C. Power down all blades that would connect to the X-Fabric modules.
  • D. Disconnect device connector.
  • E. Disconnect cabling between IFMs and fabric interconnects.

Answer: A,C

Explanation:
Before adding the X9516 X-Fabric module, the affected X-Series blades must be powered down because the X-Fabric connectivity path requires hardware installation and cannot be safely introduced while the connected compute nodes are running. The UCS PCI Mezzanine cards must also be installed in the blades so they can physically connect through the X-Fabric module to the X580p PCIe nodes for GPU expansion.


NEW QUESTION # 34
What is a purpose of Cisco AI PODs?

  • A. to deliver modular AI hardware components that can be integrated with third-party software platforms
  • B. to enable AI lifecycle management through cloud-native software with hardware support limited to compute servers
  • C. to offer a flexible AI infrastructure focused on inferencing workloads with optional training capabilities
  • D. to provide a turnkey, full-stack infrastructure for AI training, fine-tuning, and inferencing

Answer: D

Explanation:
Cisco AI PODs are designed as integrated, validated full-stack infrastructure solutions that combine compute, networking, storage, and management capabilities to support AI training, fine- tuning, and inferencing workloads with faster deployment and operational consistency.


NEW QUESTION # 35
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