Model the system
Translate an ML workload into providers, resources, variables, outputs, and state.
Practical IaC for ML platforms
Provision repeatable AI infrastructure—without treating the cloud console as source control.
This course focuses on Terraform decisions that matter to an AI engineer: GPU capacity, data boundaries, experiment environments, IAM, cost controls, and safe delivery of inference systems.
Make it reusable
Compose environment modules and protect shared state, secrets, and access paths.
Ship responsibly
Review plans in CI, constrain blast radius, and clean up ephemeral compute.