AINS graduate course

AINS6010 · Sovereign AI

Certificate line · 2026–27

Description

Stackable certificate on running capable AI under institutional control: data sovereignty and residency, on-premises and edge deployment, air-gapped or region-bound operation, and secure lifecycle practices—so teams can deliver AI without surrendering custody of models, telemetry, or policy to external clouds by default.

Course shells on the Castalia LMS are provisioned per license; this link opens the LMS to explore the guest demo or landing experience.

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Syllabus outline

  1. Modules 1–2 · Sovereignty & strategy

    • What “sovereign AI” means for data, models, and infrastructure
    • Cloud vs on-prem vs edge tradeoffs; residency and compliance hooks
    • Risk framing: supply chain, vendor lock-in, and exit plans

  2. Modules 3–4 · Engineering stack

    • Hardware classes: CPU, GPU, NPU, embedded; power and latency budgets
    • Packaging: containers, reproducible runtimes, quantization where needed
    • Serving, rollback, and observability for controlled environments

  3. Modules 5–6 · Governance & operations

    • Threat modeling for on-prem models and sensitive data
    • Updates, patching, and incident response without public-cloud assumptions
    • Hands-on labs with representative sovereign/local stacks