Course overview
This course provides a comprehensive introduction to the foundational infrastructure and operational workflows of modern AI networks. Designed for professionals who need to support AI workloads, it covers hardware foundations, real-time data pipelines, containerized model orchestration, and advanced observability. You will learn how to design networks for GPU clusters, scale data ingestion, manage model registries, and detect data drift in production environments.
- Understand the physical and virtual network requirements of high-performance GPU clusters
- Design real-time data pipelines that ingest and process unstructured data for model inference
- Deploy and orchestrate containerized models using canary strategies and model registries
- Implement observability frameworks to monitor latency, throughput, and model drift in real time