Certified AI Infrastructure & Scaling Engineer

• Plan model serving, gateways, routing, vector, and feature infrastructure
• Optimize GPU usage, batching, quantization, latency, and unit economics
• Operate inference systems with observability, load tests, and reliability plans

Platform engineers, MLOps engineers, and infrastructure teams scaling model serving under cost and latency constraints.

• Serving Architecture

  Model Serving Foundations

• Model Gateways and Routing

  Model Serving Foundations

• GPU Scheduling

  GPU and Inference Optimization

• Quantization and Batching

  GPU and Inference Optimization

• Observability for Inference

  Platform Operations

• Hands-on capstone: Design an inference platform with model routing, GPU scheduling, optimization controls, observability, and capacity runbooks.
• Final quiz checks understanding across every module.
• Public credential ID makes the result easy to verify.