Implementing Cisco Data Center AI Infrastructure CI-DCAI-QA

CI-DCAI-QA
Cena na vyžiadanie

This course provides a comprehensive introduction to designing, implementing, operating, and troubleshooting AI-enabled data centre infrastructure using Cisco technologies. Learners will explore how artificial intelligence and machine learning workloads influence modern data centre design, networking, compute, and storage decisions.The course focuses on the practical requirements of supporting AI workloads at scale, including high-performance networking, workload placement, security, sustainability, and day-two operations. Learners will examine how AI infrastructure is monitored and optimised using telemetry, analytics, and automation tools, alongside hands-on exposure to troubleshooting techniques for complex AI and machine learning environments.

Describe key artificial intelligence concepts, including traditional AI, machine learning, deep learning, and generative AI, and explain their impact on data centre infrastructure
Explain how AI technologies enhance network operations through automation, predictive analytics, and anomaly detection
Describe the architecture and operational principles of AI and machine learning clusters, including model acquisition, optimisation, and lifecycle management
Identify the essential components required to build robust, scalable, and sustainable AI infrastructure
Design and evaluate workload placement strategies to ensure performance, interoperability, and cost efficiency
Explain the network requirements for AI workloads, including transport technologies, congestion management, and lossless fabric design
Monitor, operate, and troubleshoot AI infrastructure using telemetry, analytics, and modern observability tools

Implementing Cisco Data Center AI Infrastructure

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