AI & Generative AI
Learn Cloud AI Services
Cloud AI services such as AWS Bedrock and Azure AI give you access to hosted large models through an API, so you do not run model infrastructure yourself.
Why teams use it
- No GPU infrastructure to provision or maintain.
- Data handling and regional controls are part of the managed service.
- You can compare several models behind one integration.
Where you will meet it
A company that cannot send data to a public consumer AI tool can often still use a managed model inside its own cloud account.
What to learn, and in what order
Work through these roughly in order. Jumping to the advanced list before the basics are solid is the most common way people get stuck.
Beginner
- What a managed model service provides
- Making your first call
- Choosing a model
Intermediate
- Prompt and response handling
- Cost and token tracking
- Access control
Advanced
- Private networking
- Evaluation across models
- Production monitoring
Have a project worth talking through?
Tell us what you're building or what's slowing your current system down. We'll give you a direct read on scope and approach.