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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
- Technical interpretation of prohibited practices under Article 4
- Translating legal requirements into concrete engineering controls
Secure and Compliant Development Lifecycle
- Repository structure and policy-as-code approaches for AI projects
- Code review and automated static analysis for identifying risky patterns
- Dependency and supply-chain management for model components
CI/CD Pipeline Design for Compliance
- Defining pipeline stages: build, test, validation, package, and deploy
- Integrating governance gates and automated policy checks
- Ensuring artifact immutability and provenance tracking
Model Testing, Validation, and Safety Checks
- Implementing data validation and bias detection tests
- Assessing performance, robustness, and adversarial resilience
- Defining automated acceptance criteria and test reporting mechanisms
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 and generating audit-ready artifacts
Runtime Controls, Monitoring, and Observability
- Instrumenting systems for logging inputs, outputs, and decision-making
- Monitoring model drift, data drift, and key performance metrics
- Implementing alerting, automated rollback, and canary deployment strategies
Security, Access Control, and Data Protection
- Applying least-privilege IAM policies for model training and serving environments
- Securing training and inference data both at rest and in transit
- Managing secrets and enforcing secure configuration practices
Auditability and Evidence Collection
- Generating machine-readable logs and 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 governance bodies and regulators
Summary and Next Steps
Requirements
- A solid grasp of software development and deployment workflows
- Experience with containerization and foundational 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 managing deployment processes
- Administrators overseeing 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 3200 € + VAT*
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