Course Description
The FinOps for AI Foundation course introduces learners to the discipline of financial operations as applied to artificial intelligence workloads, where the ability to forecast, monitor, and optimize AI compute and model costs directly impacts an organization’s return on its AI investment. Through hands-on exercises, case studies, and guided practice, participants will explore how to track spend across training and inference, allocate costs across teams, and balance performance against budget in cloud and on-premises AI environments.
Learners will gain an understanding of AI cost drivers, cloud pricing models, and the collaboration required between finance, engineering, and product teams to govern AI spend responsibly. By the end of the course, participants will have developed a strong foundation in FinOps for AI and the confidence to apply these skills in both professional and strategic planning settings.
Learning Outcomes
By completing this course, learners will be able to:
- Understand the key cost drivers of AI training, fine-tuning, and inference workloads.
- Design cost allocation and chargeback models tailored to specific teams and projects.
- Apply optimization strategies, including model right-sizing, caching, and spot/reserved capacity planning.
- Recognize and mitigate cost risks such as runaway inference spend and idle GPU capacity.
- Use FinOps practices to enhance decision-making in real-world applications such as budgeting, vendor negotiation, and capacity planning.
Who Should Enroll
- Students and professionals interested in AI, cloud finance, and cost governance.
- Finance and procurement teams overseeing AI and cloud budgets.
- Engineers and architects responsible for AI infrastructure and cost efficiency.
- Beginners with no prior finance or coding background, as well as those seeking to strengthen their applied FinOps knowledge.
Syllabus
- Foundations of FinOps for AI
- AI Cost Drivers & Pricing Models
- Cost Allocation & Chargeback
- Optimization Techniques for Training & Inference
- Forecasting & Budgeting for AI Workloads
- Governance, Reporting & Tooling
- FinOps for AI in Enterprises
Pre-requisites: None
