AI Solutions on Cisco Infrastructure Essentials (DCAIE) 1.0 Course
- Duration: 32 Hours
- Exam Voucher: Yes
- Language: English
- Course Delivery : E - Learning Access
9000+ Professionals Enrolled
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Course Overview
The AI Solutions on Cisco Infrastructure Essentials Course delivers foundational training for professionals responsible for preparing and operating infrastructure that supports artificial intelligence workloads. Participants gain a structured understanding of how AI applications place unique demands on compute, networking, storage, and security components. The course introduces AI workload patterns, infrastructure design considerations, and operational awareness required to ensure performance, scalability, and reliability. Practical discussions and guided examples reinforce how Cisco infrastructure components align to support modern AI environments in enterprise and data center contexts.
Course Details
- Build foundational understanding of AI workloads and infrastructure requirements.
- Learn how networking, compute, and storage support AI solutions.
- Understand infrastructure readiness considerations for AI deployments.
- Gain insight into high-performance networking concepts for AI traffic.
- Improve operational awareness of AI infrastructure performance and reliability.
- Establish a strong foundation for advanced AI, data center, and infrastructure learning paths.
- Ideal for network engineers, data center engineers, infrastructure architects, and IT professionals.
- Suitable for professionals new to AI infrastructure concepts.
- Recommended to have basic knowledge of networking and data center fundamentals.
- No prerequisite certifications required for course participation.
- Explain AI workload characteristics and their impact on infrastructure design.
- Describe the role of networking, compute, and storage in AI environments.
- Identify infrastructure readiness requirements for AI deployments.
- Understand performance, scalability, and resiliency considerations for AI solutions.
- Recognize security and operational challenges associated with AI workloads.
- Prepare for advanced training in AI infrastructure and enterprise AI solutions.
- AI Infrastructure Fundamentals: AI workloads and deployment models.
- Compute and Acceleration Awareness: CPUs, GPUs, and accelerators for AI.
- High-Performance Networking Concepts: Bandwidth, latency, and traffic patterns.
- Storage Considerations for AI: Data access, throughput, and scalability.
- Infrastructure Readiness: Designing environments for AI performance and growth.
- Security and Operations: Protecting and operating AI infrastructure.
- Operational Best Practices: Monitoring, maintenance, and optimization awareness.
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