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Duration 14 hours
Course Outline
Foundations: The EU AI Act for Technical Teams
- Relevant obligations and key terminology for developers and operators.
- A technical perspective on understanding prohibited practices under Article 4.
- Translating legal requirements into actionable engineering controls.
Secure and Compliant Development Lifecycle
- Structuring repositories and implementing policy-as-code for AI projects.
- Conducting code reviews and applying automated static checks for risky patterns.
- Managing dependencies and supply-chain integrity for model components.
CI/CD Pipeline Design for Compliance
- Defining pipeline stages: build, test, validation, package, and deploy.
- Integrating governance gates and automated policy verification.
- Ensuring artifact immutability and maintaining provenance tracking.
Model Testing, Validation, and Safety Checks
- Implementing data validation and bias detection tests.
- Assessing performance, robustness, and adversarial resilience.
- Establishing automated acceptance criteria and generating test reports.
Model Registry, Versioning, and Provenance
- Utilizing MLflow or equivalent tools for model lineage and metadata management.
- Versioning models and datasets to ensure reproducibility.
- Recording provenance data and generating 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.
- Implementing alerting systems, automated rollback, and canary deployments.
Security, Access Control, and Data Protection
- Enforcing least-privilege IAM for model training and serving environments.
- Safeguarding training and inference data both at rest and in transit.
- Applying secrets management and secure configuration best practices.
Auditability and Evidence Collection
- Generating machine-readable logs alongside human-readable summaries.
- Packaging evidence for conformity assessments and regulatory audits.
- Defining retention policies and ensuring secure storage of compliance artifacts.
Incident Response, Reporting, and Remediation
- Identifying suspected prohibited practices or safety incidents.
- Executing technical steps for containment, rollback, and mitigation.
- Drafting technical reports for governance bodies and regulators.
Summary and Next Steps
Requirements
- A solid grasp of software development and deployment lifecycles.
- Proficiency with containerization and foundational Kubernetes concepts.
- Working knowledge of Git-based source control and CI/CD methodologies.
Target Audience
- Developers creating or maintaining AI-based components.
- DevOps and platform engineers overseeing deployment processes.
- Administrators responsible for managing infrastructure and runtime environments.
