• Fundamentals of AI
• Generative AI
• AI Use Cases
• AI-ML Clusters and Models
• AI Toolset Mastery - Jupyter Notebook
• AI Infrastructure
• AI Workload Placements and Interoperability
• AI Policies
• AI Sustainability
• AI Infrastructure Design
• Key Network Challenges and Requirements for AI Workloads
• AI Transport
• Connectivity Models
• AI Network
• Architecture Migration to AI/ML Network
• Application-Level Protocols
• High Throughput Converged Fabrics
• Building Lossless Fabrics
• Congestive Visibility
• Data Preparation for AI
• AI/ML Workload Data Performance
• AI-Enabling Hardware
• Compute Resources
• Compute Resource Solutions
• Virtual Resources
• Storage Resources
• Setting Up AI Cluster
• Deploy and Use Open Source GPT Models for RAG

• Network Designers
• Network Administrators
• Storage Administrators
• Network Engineers
• Systems Engineers
• Data Center Engineers
• Consulting Systems Engineers
• Technical Solutions Architects
• Cisco Integrators/Partners
• Field Engineers
• Server Administrators
• Network Managers
• Program Managers
• Project Managers

There are no prerequisites for this training. This is an essentials training that progresses from beginner to intermediate content. Familiarity with Cisco data center networking and computing solutions is a plus but not a requirement. However, the knowledge and skills you are recommended to have before attending this training are:

• Cisco UCS compute architecture and operations
• Cisco Nexus switch portfolio and features
• Data Center core technologies

These skills can be found in the following Cisco Learning Offerings:

• Introducing Cisco Unified Computing Systems (DCIUCS)
• Implementing Cisco NX-OS Switches and Fabrics in the Data Center (DCNX)
• Implementing Cisco Data Center Core Technologies (DCCOR)