Schulungsübersicht
Understanding AI and Machine Learning
- What is AI and how is it defined?
- Machine Learning as a subset of AI
- Types of AI: weak, strong, generative, supervised, unsupervised
AI in Practice Across the Organization
- Where AI/ML currently exists in business functions
- Automation, decision support, customer service, and analytics
- Use cases in HR, finance, operations, and compliance
Common Governance Challenges
- Conflicts with the Data Protection Principles
- Lawfulness, fairness, and transparency in automated decision-making
- Accuracy, data minimization, and storage limitations
Foundations in Information and Data Management
- Information and records management in AI contexts
- The importance of metadata and audit trails
- Maintaining data quality and integrity for training datasets
Approaching Information Governance Challenges
- Designing governance controls for AI/ML pipelines
- Human oversight and explainability
- Building cross-functional governance teams
Conducting DPIAs for AI/ML
- Legal requirement and purpose of DPIAs
- Steps to assess proposed AI/ML implementations
- Documenting risk assessments, mitigations, and justifications
Governance Frameworks and Risk Management
- Overview of AI-specific governance frameworks
- ISO, NIST, ICO, and OECD approaches
- Risk registers and policy documentation
Culture, Integration, and Related Frameworks
- Embedding a culture of responsible AI use
- Linking AI governance with cybersecurity, ethics, and ESG policies
- Continuous improvement and monitoring
Summary and Next Steps
Voraussetzungen
- An understanding of organizational information governance policies
- Familiarity with data protection or privacy regulations
- Some exposure to AI or machine learning concepts is helpful
Audience
- Information governance professionals
- Data protection officers and compliance managers
- Digital transformation or IT governance leads
Erfahrungsberichte (2)
das ML-Ekosystem, nicht nur MLFlow sondern auch Optuna, Hyperopt, Docker und Docker-Compose
Guillaume GAUTIER - OLEA MEDICAL
Kurs - MLflow
Maschinelle Übersetzung
Ich habe es sehr genossen, an der Kubeflow Ausbildung teilzunehmen, die ferngesteuert durchgeführt wurde. Diese Ausbildung ermöglichte mir, mein Wissen zu AWS-Diensten, K8s und allen devOps-Tools rund um Kubeflow zu festigen, was die notwendige Grundlage ist, um das Thema angemessen anzugehen. Ich möchte Malawski Marcin für seine Geduld und Professionalität bei der Ausbildung sowie für Tipps zur besten Praxis danken. Malawski attackiert das Thema aus verschiedenen Perspektiven, mit unterschiedlichen Bereitstellungstools Ansible, EKS kubectl, Terraform. Jetzt bin ich definitiv überzeugt, dass ich mich auf dem richtigen Anwendungsgebiet befinde.
Guillaume Gautier - OLEA MEDICAL | Improved diagnosis for life TM
Kurs - Kubeflow
Maschinelle Übersetzung