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Beginnt 6 June 2026 13:43
Endet 6 June 2026
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22 minutes
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Übersicht
Lehrplan
- Introduction to AI Guardrails
- Understanding Hybrid Vector Spaces
- Designing Guardrails for AI Agents
- Building Chatbot Guardrails
- Tools and Techniques for Guardrails Implementation
- Case Studies and Applications
- Challenges and Future Directions
- Capstone Project
- Review and Conclusion
Overview of AI systems and need for guardrails
Introduction to hybrid vector space in AI
Basics of vector space models
Combining symbolic and vector-based methods
Applications in AI guardrails
Principles of effective guardrails
Identifying constraints: brand, topic, and behavior
Specific use-cases for chatbots
Developing brand-specific constraints
Topic-based guardrails in natural language processing
Implementing behavioral constraints
Popular tools and libraries
Integrating guardrails with existing systems
Monitoring and testing guardrails effectiveness
Real-world examples of guardrail implementations
Lessons learned from brand-specific deployments
Limitations of current guardrail techniques
Innovations in hybrid vector space for evolving AI needs
Designing and implementing guardrails for a sample AI chatbot
Presentation and feedback analysis
Recap of key concepts and skills
Future learning paths and resources for continued education
Fachgebiete
Computer Science