AI curriculum
Course outline for Owning the AI Stack
AI sourcing decisions shape control over data, costs, and operations. Compare hosted and self-managed options to make ownership and vendor trade-offs explicit.
About Owning the AI Stack
AI sourcing decisions shape control over data, costs, and operations. Compare hosted and self-managed options to make ownership and vendor trade-offs explicit.
Owning the AI Stack Course Objectives
- Compare SaaS, API, and self-hosted operating models.
- Identify data ownership and vendor dependence risks.
- Build a decision matrix with cost, security, and control criteria.
Pre-requisites
- Familiarity with technology purchasing or product decisions.
- Basic AI awareness; no coding experience is required.
Lab Setup
- Computer with a spreadsheet and document editor.
- Use supplied architecture and cost scenarios; no cloud account, model download, or paid service is necessary.
Detailed Course Outline
Proposed modulesModule 1: Sourcing models
- SaaS vs API vs self-hosting
- Open vs closed models
- Local models
- Small language models
Practical outcome: Compare sourcing options for a defined workload.
Module 2: Ownership boundaries
- Infrastructure ownership
- Data ownership
- Vendor dependence
Practical outcome: Record operating responsibilities and exit constraints.
Module 3: Strategic decisions
- Cost
- Security
- Strategic control
Practical outcome: Weight decision criteria and document remaining uncertainties.
Practical exercise
- Produce an AI stack decision matrix and an exit plan for a fictional organization.
How we train
Contact us for full course details, including duration, delivery options and lab requirements.
Ask about exercises, instructor feedback and the prior knowledge you need. Tool-specific courses marked provisional may become modules in a broader course.
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