Self-paced online course
Learn to manage
the cost of AI.
A self-paced online course that teaches you how to measure AI spend, explain what drives it, and make better cost and quality decisions across models, RAG and agents.
Every chapter free • Beginner-friendly • Learn at your own pace
Designed for FinOps practitioners, engineers, product managers and finance teams.
Chapter 01 · Foundations
Understanding AI costs
Learn how requests, tokens and model choices appear on an AI bill.
In this lesson
- Trace how AI usage becomes cost
- Read token and model pricing
- Compare cost with quality
Worked example
Trace a real AI bill line by line
Applied skills
What you will be able to do
Make cost decisions that engineering and finance can both trust.
Practical, not theoretical
Work with the evidence behind the bill.
Use realistic datasets, provider bills, API usage events, prompt examples, cost incidents and business scenarios. Every exercise works with spreadsheets and sample data, so paid tools and provider access are optional.
Course roadmap
Every chapter is free to read.
See the complete path from cloud cost foundations to AI governance. Chapters are released as they are ready, and all of them stay free.
Part 1 · Foundations
FinOps Crash Course
Part 2 · Build AI cost visibility
From API Calls to Business Workloads
AI Usage Telemetry and Cost Allocation
Dashboards, KPIs and Cost Anomalies
Part 3 · Optimize AI workloads
Prompt, Context and Output Waste
Caching Economics and Avoidable Uncached Spend
Model Rightsizing and Workload Routing
Compare Models Without Breaking Production
Part 4 · Advanced AI cost drivers
RAG and Embedding Economics
Agent Economics and Cost Controls
Part 5 · Operate AI FinOps
Forecasting, Budgets and AI Unit Economics
Governance and the AI FinOps Operating Model
Part 6 · Reference
Glossary Work in progress
Capstone preview
Reduce an AI bill without breaking the application.
Investigate why a fictional AI bill rose from $18,420 to $31,760 while usage grew only 24%.