01 — Analyze Requirements and Design Generative AI Solutions

01 — Analyze Requirements and Design Generative AI Solutions

Module Introduction

• Introduction
• Exploring generative AI capabilities
• Core capabilities of generative A
• The generative AI developer role
• Key topics

Foundation Model Introduction

• Introduction
• Foundation model core concepts
• Model types and selection
• Integration and deployment approaches
• Model chaining and orchestration
• Real-world implementation

Fundamentals Of Amazon Bedrock Poc Design

• Introduction
• Amazon Bedrock capabilities overview
• API integration options
• Prompt engineering fundamentals
• PoC scoping methodology
• Technical validation approaches
• Model selection methodology
• Authentication and security considerations
• Performance testing framework
• Value calculation techniques
• Process automation benefits
• Business impact assessment
• Real-world implementation

From Poc To Production

• Introduction
• Production readiness assessment
• Building production mechanisms
• Components of effective mechanisms
• Production deployment patterns
• RAG production challenges and solutions
• Enterprise adoption strategy
• Production monitoring and optimization
• Implementation roadmap
• Risk mitigation strategies
• Production readiness checklist

Well-architected Framework Foundations For Generative Ai Applications

• Introduction
• The Six Pillars of AWS Well-Architected Framework
• AWS Well-architected tool overview
• Generative AI lens deep dive
• Standardizing AI component implementation
• Implementation roadmap

Cross-deployment Standardization

• Introduction
• Standardized component templates
• Validation mechanisms
• Documentation and governance
• Multi-region deployment considerations
• Implementation best practices
• Component design principles
• Testing and validation strategies

Module Summary

• Recap and next steps
• Resources