Amazon Bedrock and Foundation Models
Description
Comprehensive mastery of Amazon Bedrock service for accessing, deploying, and managing foundation models from leading AI providers including Amazon Titan, Anthropic Claude, and other model families.
Learning Objectives
Learners will master Amazon Bedrock architecture, foundation model selection and access, model customization using Bedrock APIs, security and compliance features, cost optimization strategies, and integration patterns with other AWS services. They will understand how to deploy and manage enterprise-grade generative AI applications using Bedrock's managed foundation models.
Topics (10)
Comprehensive overview of Amazon Bedrock service, its architecture, benefits, and position in the AWS AI/ML service portfolio.
Detailed study of available foundation models, model comparison, selection criteria, and evaluation techniques within Bedrock.
Detailed study of partner foundation models, their unique capabilities, strengths, and optimal use cases within the Bedrock ecosystem.
Hands-on exploration of Bedrock APIs, SDK usage, authentication, request/response handling, and error management.
Comprehensive study of Bedrock's model customization features, fine-tuning processes, and custom model deployment.
Study of Bedrock Agents architecture, workflow orchestration, Knowledge Bases integration, and RAG implementation patterns.
Comprehensive coverage of Bedrock security architecture, IAM integration, data encryption, compliance certifications, and governance features.
Detailed study of Bedrock pricing structure, cost monitoring, optimization techniques, and budget management strategies.
Comprehensive study of AWS service integration patterns, serverless architectures, data pipeline integration, and monitoring solutions.
Comprehensive coverage of Amazon Titan model suite, capabilities, use cases, and integration patterns for enterprise applications.