AICCI AI Practitioner

• (Future) AI officers and AI compliance officers
• AI coordinators and managers
• Employees who implement or operate an AI management system
• Professionals and executives who want to establish a legally compliant and responsible use of AI

Module 1 - Overview of AI technologies and application architectures

• Classification: traditional AI, machine learning, deep learning, generative AI
• Typical architectural components of AI systems
• Overview of common AI frameworks and platforms (without coding exercises)
• Criteria for tool selection based on project requirements

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Module 2 - Data as the foundation of AI

• Data types and sources (structured and unstructured)
• Basics of data preparation (cleaning, labeling, transformation)
• Data quality and data governance
• Ethical aspects and data protection in data usage

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Module 3 - Model types and selection criteria

• Supervised, unsupervised, and reinforcement learning — conceptual comparison
• Overview of common model families (decision trees, linear models, neural networks, transformers)
• Selecting suitable models for specific use cases
• Trade-offs: accuracy, computational effort, interpretability

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Module 4 - Generative AI in practice

• Basics of generative models (text, image, audio, video)
• Prompt engineering as a strategic tool
• Integration of LLMs into applications via APIs (conceptual)
• Typical use cases and limitations

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Module 5 -Testing, validating, and optimizing

• Evaluation metrics for AI models (accuracy, precision, recall, F1-score) — explained conceptually
• Avoiding overfitting and bias
• Iterative improvement process
• Documentation and traceability

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Module 6 - Deployment and operations

• Transitioning from prototype to production system
• Integration into existing IT environments (conceptual overview)
• Monitoring and maintaining AI models
• Managing model aging (model drift)

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Practical workshop

• 3 hands-on exercises
• Group discussion

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Exam preparation

• Sample exam

• Participation does not require any specific prerequisites.
  
• Recommended: Basic knowledge in data analysis and understanding of fundamental IT and software concepts.
  
• Attending the AICCI AI Foundation beforehand will make it easier to get started.

• Exam format: multiple choice (one or more correct answers)
• Language: German or English
• Duration: 60 minutes
• Number of questions: 40
• Passing score: at least 65 percent correct answers