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Duration 14 hours
Course Outline
Foundations: EU AI Act for Technical Teams
- Key obligations and terminology relevant to 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
- Repository structures and policy-as-code approaches for AI projects.
- Code reviews and automated static checks for identifying risky patterns.
- Managing dependencies and the supply chain for model components.
CI/CD Pipeline Design for Compliance
- Pipeline stages: build, test, validation, packaging, and deployment.
- Integrating governance gates and automated policy verification.
- Ensuring artifact immutability and tracking provenance.
Model Testing, Validation, and Safety Checks
- Data validation and bias detection testing.
- Assessing performance, robustness, and adversarial resilience.
- Defining automated acceptance criteria and generating test reports.
Model Registry, Versioning, and Provenance
- Leveraging MLflow or equivalent tools for model lineage and metadata.
- Versioning models and datasets to ensure reproducibility.
- Documenting provenance and producing audit-ready artifacts.
Runtime Controls, Monitoring, and Observability
- Instrumentation for logging inputs, outputs, and decision-making processes.
- Monitoring model drift, data drift, and key performance metrics.
- Implementing alerting, automated rollback, and canary deployments.
Security, Access Control, and Data Protection
- Applying least-privilege IAM for model training and serving environments.
- Safeguarding training and inference data both at rest and in transit.
- Managing secrets and implementing secure configuration practices.
Auditability and Evidence Collection
- Generating machine-readable logs alongside human-readable summaries.
- Compiling evidence packages for conformity assessments and 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 governance bodies and regulators.
Summary and Next Steps
Requirements
- A solid understanding of software development and deployment workflows.
- Experience with containerisation and fundamental Kubernetes concepts.
- Familiarity with Git-based source control and CI/CD practices.
Target Audience
- Developers responsible for building or maintaining AI components.
- DevOps and platform engineers overseeing deployment processes.
- Administrators managing infrastructure and runtime environments.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 2600 € + VAT*
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