Overview
Discover how to integrate Generative AI into enterprise platforms handling petabyte-scale data, from implementation challenges to successful deployment, with insights from Dynatrace's hypermodel AI Davis.
Syllabus
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- Introduction to Generative AI
-- Overview of Generative AI technologies
-- Key concepts and use cases in enterprises
- Understanding Enterprise Data at Scale
-- Characteristics of petabyte-scale data
-- Data management strategies for large datasets
- Integrating Generative AI into Existing Platforms
-- Architecture of enterprise AI platforms
-- API integration and data pipelines
- Implementation Challenges
-- Technical challenges in scaling AI solutions
-- Data privacy and security considerations
- Insights from Dynatrace's Hypermodel AI Davis
-- Case study: AI Davis in action
-- Lessons learned from real-world deployments
- Successful Deployment Strategies
-- Best practices for Generative AI adoption
-- Metrics for evaluating AI system performance
- Advanced Generative AI Techniques
-- Machine learning models for Generative AI
-- Natural Language Processing (NLP) and image generation
- Managing AI at Scale
-- Monitoring and maintenance of AI systems
-- Continuous improvement and model updates
- Future Trends in Generative AI
-- Emerging technologies and innovations
-- Predictions for the future of AI in enterprises
Taught by
Tags
On-Demand
