AI Fundamentals and Cisco AI-Ready Infrastructure – 2 days (AI-PW2)
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Overview
Description, Pre requisites -
Content
Lessons, Course Structure -
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Date, location, Participant(s) details
Artificial intelligence (AI) is a major focus in all the sectors of industry and government. It is a rapidly evolving space with many advanced features that provide greater insight, knowledge and operational efficiencies in many areas of operation.
Many businesses have indicated that AI is a strategic objective, but few have advanced to implementation and use. The aim of this session is to explore AI concepts and how Cisco is providing an AI ready Data Center.
Objectives
- Provide an overview of the AI space and how Cisco is positioning itself in the evolving market
- Products as well as partnerships with other key players to create a framework for AI based around Cisco infrastructure
- Technologies that form the AI landscape and how Cisco infrastructure and ecosystem interact
Target audience:
- IT Architects and Designers
- Presales SEs
- Network Engineers
- Server Administrators
- AI Integrators
Pre-requisite skills:
- Network Admin skills
- Understanding of programming concepts
- Conceptual understanding of VM and containers
- Basic knowledge of Cisco UCS server environment
- Basic Linux overview
Duration:
2 days
Module 1 – AI Overview
- Changing Landscape
- AI Overview
- Who will use AI
- AI Use Cases
Module 2 – AI System Overview
- The Anatomy of an AI system
Module 3 –AI App
- AI model Overview
- AI Apps and Model integration
- AI Enhancement and Adaptation
- RAG
- Fine tuning
- AI Guardrails
- Agentic AI
- Tools
- Inferencing Process Overview
Module 4 – Cisco AI Ready DC Overview
- Cisco AI infrastructure Overview
- Cisco AI Pods
- Cisco Hyperfabric AI
Module 5 – Cisco AI Partners
- NVIDIA Offerings
- RedHat OpenShift Overview
- Storage Partners
- Opensource Community
Module 6 – Cisco AI Hosts
- Cisco UCS portfolio
- UCS-X series
- UCS C885A and C845A
- UCSI C-series
Module 7 – GPUs
- Architecture and Functional Overview
- Core
- vRAM
- NVIDIA Product range
- UCS GPU options
- GPU sharing
- GPU Scoping
- Model serving
- GPU scoping parameters
- Sizing tools
- Host requirements
Module 8 – AI Host Networking
- GPU Clustering
- GPU to GPU connectivity
- Intra Node GPU clustering
- NVLink
- Inter Node GPU clustering
- RoCE2
- Delay and throughput
- Host networking
- NICS and DPU
Module 9 – Cisco AI Networking
- AI networking overview
- Backend Network requirements
- NDFC and NXOS
- Hyperfabric AI
- AI QOS requirements
- Nexus and NDFC
- AI pod connectivity
- Nexus Smart Switches
- ND and NDFC overview
- Cisco Hyperfabric
- The road to Hyperfabric AI
- Hyperfabric Architecture and components
- Fabric Lifecycle Management
- Configuration overview
Module 10 – K8 and OpenShift Overview
- Container and Kubernetes (K8) overview
- K8 and AI
- Scalability
- HA
- Monitoring
- RedHat OpenShift Overview
- GUI
- Nodes
- Operators
- Deployment and use
- OC and YAML
- GUI
Module 11 – Model Deployment Workshop
- Building simple AI environment
- NIM provisioning
Appendixes
App 1 – AI Models
- AI model characteristics
- Architecture
- Parameters
- Accuracy
- Model Distribution
- Format
- Frameworks
- Model sources
App 2 – Cisco Host Mgmt. and Intersight
- Intersight overview
- Host and networking configuration
- Pools
- policies
- profiles
- monitoring
App 3 – Cisco Nexus and NDFC AI Fabric
- Cisco Nexus AI ready switches
- NDFC review
- Configuration overview
- Cisco Connectivity – AI POD Overview
App 4 – Cisco AI Monitoring and Security Overview
- Cisco AI Security Smart Switches
- Host and OS Security
