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Duration 14 hours
Course Outline
Foundations: The EU AI Act for Technical Teams
- Key obligations and terminology relevant to developers and operators.
- Technical interpretation of prohibited practices under Article 4.
- Translating legal requirements into actionable engineering controls.
Secure and Compliant Development Lifecycle
- Repository structure and policy-as-code implementation for AI projects.
- Code reviews and automated static analysis to detect risky patterns.
- Managing dependencies and supply chains for model components.
CI/CD Pipeline Design for Compliance
- Defining pipeline stages: build, test, validation, packaging, and deployment.
- Integrating governance gates and automated policy checks into the workflow.
- Ensuring artifact immutability and tracking provenance.
Model Testing, Validation, and Safety Checks
- Executing data validation and bias detection tests.
- Assessing performance, robustness, and adversarial resilience.
- Defining automated acceptance criteria and generating test reports.
Model Registry, Versioning, and Provenance
- Leveraging MLflow or similar tools for model lineage and metadata management.
- Versioning models and datasets to ensure reproducibility.
- Recording provenance and creating audit-ready artifacts.
Runtime Controls, Monitoring, and Observability
- Instrumenting systems to log inputs, outputs, and decision-making processes.
- Monitoring model drift, data drift, and key performance metrics.
- Configuring alerting, automated rollback, and canary deployment strategies.
Security, Access Control, and Data Protection
- Implementing least-privilege IAM for model training and serving environments.
- Safeguarding training and inference data both at rest and in transit.
- Managing secrets and adhering to secure configuration practices.
Auditability and Evidence Collection
- Generating machine-readable logs alongside human-readable summaries.
- Packaging evidence for conformity assessments and regulatory audits.
- Establishing retention policies and secure storage for compliance artifacts.
Incident Response, Reporting, and Remediation
- Detecting suspected prohibited practices or safety incidents.
- Executing technical steps for containment, rollback, and mitigation.
- Preparing technical reports for internal governance and regulators.
Summary and Next Steps
Requirements
- A solid understanding of software development and deployment workflows.
- Experience with containerization and foundational Kubernetes concepts.
- Familiarity with Git-based source control and CI/CD practices.
Audience
- Developers building or maintaining AI components.
- DevOps and platform engineers responsible for deployment.
- Administrators managing infrastructure and runtime environments.
