Models need somewhere to train and run, and clicking through a cloud console to create that somewhere does not scale. Environments drift, nobody remembers exactly what was set up, and rebuilding after a failure becomes guesswork. Infrastructure as Code (IaC) fixes this by describing servers, networks, and storage in files that live in version control, just like application code.
You'll start with what IaC is and why teams use it, then learn Terraform: providers, resources, and state. From there you'll move to longer hands-on courses that provision real infrastructure on AWS, the kind of setup an ML team needs for training and serving.
With reproducible infrastructure in place, you can build the workflows that run on it. The next module, ML Pipelines & Feature Stores, covers automating training and managing the features models depend on.
The foundations of infrastructure as code and why it matters, as the first lesson of a Terraform beginner series.
A beginner tutorial on the concept of IaC and why it is changing how teams manage infrastructure, with Terraform as the example.
A fast tour of Terraform basics: Infrastructure as Code, providers, resources, and state management.
A complete beginner course on using Terraform, an open-source infrastructure as code tool, to manage AWS infrastructure.
Automate AWS infrastructure with Terraform, from getting started to a modular, automated system using GitHub.