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Cisco 300-640 Exam Syllabus Topics:

SectionObjectives
Data Center AI Infrastructure Fundamentals- AI/ML workload requirements in data centers
  • 1. Compute, GPU, and acceleration concepts
    • 2. Data pipeline and workload characteristics
      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 Nexus platform concepts
            • 2. Cisco ACI integration concepts
              Security and Governance in AI Data Centers- Infrastructure security
              • 1. Network segmentation and policy enforcement
                • 2. Secure access to AI workloads
                  Compute and Storage for AI Infrastructure- Storage systems
                  • 1. Distributed storage concepts
                    • 2. High-throughput storage for AI training data
                      - Compute architecture
                      • 1. GPU-based compute nodes
                        • 2. HPC-style scaling considerations
                          AI Infrastructure Deployment and Operations- Deployment models
                          • 1. On-premises AI clusters
                            • 2. Hybrid AI infrastructure integration
                              - Operations and lifecycle management
                              • 1. Monitoring and observability
                                • 2. Performance tuning and optimization

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                                  Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions (Q35-Q40):

                                  NEW QUESTION # 35
                                  What describes inference traffic patterns in AI deployments?

                                  Answer: D

                                  Explanation:
                                  Inference traffic is associated with using a trained model to generate predictions or responses from new input data. In AI deployments, this commonly supports real-time or near-real-time decision making, such as classification, recommendations, detection, or automated responses.


                                  NEW QUESTION # 36
                                  A customer deploys a UCS 885a server in a data center with two power grids. Three of the
                                  3000W power supplies in the server connect to each grid. Due to an external event, one of the grids will be shut down for maintenance. How does the server respond to this event?

                                  Answer: D

                                  Explanation:
                                  With three 3000W power supplies lost from one power grid, the UCS C885A continues operating on the remaining grid but no longer has the full power budget available for maximum GPU operation. The server reduces performance by enforcing power limits, including capping GPU power, so workloads can continue running within the available power capacity.


                                  NEW QUESTION # 37
                                  A medical company has existing third-party AI servers and NVMe storage, but they want to purchase Cisco network switches with a cloud managed feature for simplicity. Which solution best meets the requirements?

                                  Answer: A

                                  Explanation:
                                  Bring Your Own AI HyperFabric is the best fit when the customer already has third-party AI servers and NVMe storage but wants Cisco 6000 Series switching with simplified cloud-managed fabric operations. The Premier license aligns with the AI-focused HyperFabric use case, while Cisco describes Nexus HyperFabric as a cloud-managed AI infrastructure solution using Cisco
                                  6000 Series switches for AI workloads.


                                  NEW QUESTION # 38
                                  Which function is provided through natural language processing?

                                  Answer: C

                                  Explanation:
                                  Natural language processing enables systems to interpret, process, and transform human language from spoken or written inputs into structured data that applications can analyze, search, classify, or use for automation.


                                  NEW QUESTION # 39
                                  A bank is planning to deploy an AI inference solution at its branch locations. The solution must support workloads that require a balance of compute, memory, and potential GPU acceleration, and it must be suitable for installation by nontechnical onsite resources. The requirements are:
                                  - high availability of the chassis management plane.
                                  - support for up to 768 GB of memory for in-memory model storage and
                                  processing
                                  - remote server launch requiring no on-site IT staff
                                  - use of Cisco Intersight for SaaS-based infrastructure lifecycle
                                  management
                                  Which solution meets the requirements?

                                  Answer: D


                                  NEW QUESTION # 40
                                  ......

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