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Cisco 300-640 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Infrastructure Fundamentals | 20% | - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Explain Cisco AI infrastructure solutions and portfolio - Describe AI and machine learning concepts - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Describe AI use cases in data center environments |
| Topic 2: AI Infrastructure Operations and Troubleshooting | 20% | - Manage health, logs, and events - Troubleshoot network, compute, storage, and orchestration issues - Implement performance benchmarking and validation - Optimize performance, security, and reliability - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts |
| Topic 3: AI Infrastructure Deployment and Data Management | 30% | - Implement data management and lifecycle for AI workloads - Integrate AI frameworks and applications with Cisco infrastructure - Deploy and manage AI infrastructure with orchestration tools - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics |
| Topic 4: AI Infrastructure Components and Architecture | 30% | - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate hybrid and multi-cloud AI integration - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability - Evaluate power, cooling, and efficiency requirements - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures |
Cisco Implementing Cisco Data Center AI Infrastructure Sample Questions:
1. What is a purpose of Cisco AI PODs?
A) to enable AI lifecycle management through cloud-native software with hardware support limited to compute servers
B) to offer a flexible AI infrastructure focused on inferencing workloads with optional training capabilities
C) to provide a turnkey, full-stack infrastructure for AI training, fine-tuning, and inferencing
D) to deliver modular AI hardware components that can be integrated with third-party software platforms
2. Drag and Drop Question
An organization is deploying an AI/ML infrastructure with multiple network fabrics, each serving a specific purpose. The network architect must match the network fabric type with its primary function. Drag and drop the network fabric types from the left onto the corresponding descriptions on the right.
3. A network engineer must secure management access to Cisco Nexus AI switches. Which protocol should replace Telnet to provide encrypted administrative sessions?
A) TFTP
B) FTP
C) SNMPv1
D) SSH
4. A network engineer logs into Nexus Dashboard and sees an anomaly showing that a BGP peer connection has gone down. Next to the anomaly, a yellow bubble displays "Correlated." What does Nexus Dashboard indicate by "Correlated" in this case?
A) It indicates that the Nexus Dashboard has correlated the scope of the impact.
B) It indicates that the Nexus Dashboard has seen this anomaly across more than one device in the fabric.
C) It indicates that this anomaly is a result of a higher-level root anomaly.
D) It indicates that the Nexus Dashboard has correlated this anomaly to activity by specific user account.
5. An Intersight administrator plans to deploy new server solutions to several small branch offices across the country. Each location needs at least one chassis. The servers must have redundant CPUs, memory, and 200 Gbps of unified fabric connectivity per compute node. Which hybrid AI compute solution meets the requirements?
A) Cisco UCS X-Direct
B) Cisco UCS C885A M8
C) Cisco UCSXE Unified Edge
D) Cisco UCS S3260
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: Only visible for members | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: A |
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