Cisco Designing Cisco Systems for AI (DCSAI)

Agenda

Module 1: Introduction to AI and Network Design

• Understanding the emergence of AI and its practical applications
• Overview of Cisco technologies for AI integration
• Challenges and considerations in designing AI-ready networks

Module 2: Understanding the components if AI Infrastructure

• High Performance GPU Cloud
• High Performance Storage and Storage Networks
• High Performance Ethernet Networks
• High Performance Compute
• Data Processing and Machine Learning Frameworks
• MLOps Platforms

Module 3: Understanding AI Workloads and Network Requirements

• Kubernetes vs. Docker/Container
• Workload characterization and Generative AI Workload
• Distributed Workloads and Computing
• Network architecture requirements for AI applications
• Scalability, performance, and latency considerations
• Integration of high-speed data pipelines for AI model training and inference

Module 4: Cisco Networking Technologies for AI

• Deep dive into Cisco switches, routers, and data center fabrics
• Introduction to SONiC and SONiC on Cisco 8000
• Deep Dive into SONiC for AI Infrastructure Networking in the Hybrid Cloud Environments
• Neural Networks and Parallelism
• Cisco NDFC for network automation and policy-based management on Nexus Spine and Leaf Architecture
• Integration of Cisco UCS for AI workload optimization

Module 5: Security and Compliance for AI Networks

• Threat landscape for AI environments
• Implementing security controls for data privacy and confidentiality
• Compliance considerations for AI data handling and processing

Module 6: Network Optimization Techniques for AI

• Quality of Service (QoS) for prioritizing AI traffic
• Network slicing for efficient resource allocation
• Load balancing and traffic engineering for AI workloads

Module 7: Monitoring and Analytics for AI Networks

• Utilizing Cisco Observability Solutions for AI Networks
• AI-driven analytics for proactive network management
• MLOps Tools
• Troubleshooting and optimization techniques for AI workloads connectivity challenges

Module 8: Case Studies and Best Practices

• Real-world examples of AI network designs using Cisco technologies
• Best practices for deploying and managing AI-ready networks
• Lessons learned and future trends in AI network design

Module 9: Hands-on Labs and Practical Exercises

• Lab exercises covering network design, configuration, and optimization
• Simulation of AI workloads to test network performance
• Troubleshooting scenarios and best practices demonstration