The State of GenAI and ML in the Cloud Native Ecosystem

Übersicht

Lehrplan

• Introduction to GenAI & ML in Cloud Native Environments
Overview of Cloud Native Architectures
Definitions and Scope of GenAI and ML
• Current Trends in GenAI and ML
Adoption of GenAI and ML in Cloud Native Applications
Innovations in Language Models and Transfer Learning
• Cloud Native Tools for GenAI & ML
Overview of Kubernetes and Containerization
Microservices and Serverless Architectures
Emerging Tools and Platforms
• LLMOps/MLOps Workflows
Workflow Automation and CI/CD for ML
Model Training, Deployment, and Monitoring
Case Studies and Best Practices
• Optimization Strategies
Scalability and Performance Tuning in Cloud Environments
Cost Optimization Techniques
• AI Safety Guardrails
Ethical Considerations in AI Deployment
Implementing Security and Privacy Measures
Bias Detection and Mitigation
• Challenges in the Cloud Native GenAI & ML Ecosystem
Data Management and Governance
Integration with Legacy Systems
• Future Directions
Potential Innovations and Disruptive Technologies
Predictions for the Evolution of GenAI and ML in Cloud Native Contexts
• Course Summary and Q&A Session
Recap of Key Concepts
Open Discussion and Feedback

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Fachgebiete

Computer Science