About this course
AI and cloud spend is hard to budget because it moves with usage, not headcount. A model change, a traffic spike, or a new feature can shift the bill in days. This course teaches you how to take historical spend data, build a working budget model, and create forecasts that update with real usage — so you can explain what happened and what is coming next.
What you will learn
- How to score your current budget process and find the gaps
- How to build a budget from historical spend, category analysis, and growth assumptions
- How to create base, growth, and stress-case forecasts
- How to run a lightweight forecasting cadence without a FinOps team
How to use this course: Work through the modules in order for the full picture, or jump to the lesson that matches the problem in front of you right now. Each module is a standalone read — estimated total time is 38 minutes.
Course modules
4 lessons · 38 min total read time
Cloud and AI budget health check
Score your budget process and identify the next 30 days of improvements.
How to build an AI and cloud infrastructure budget
Use historical spend, category analysis, and growth assumptions to create a working budget model.
How to forecast AI costs in production
Build base, growth, and stress-case forecasts using request volume, unit economics, and confidence ranges.
How to forecast cloud and AI spend without a FinOps team
A lightweight forecasting approach for teams that need pace and confidence without heavy finance process.
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