Module 1: Foundation Models and Core Concepts
Introduction to AWS Generative AI ecosystem
Understanding tokenization and language models
Multi-model architectures and implementations
Retrieval Augmented Generation (RAG) fundamentals
Module 2: Amazon Q Developer Tools
Amazon Q Developer capabilities and features
IDE integration (IntelliJ, VS Code)
Code analysis and documentation assistance
Security scanning and best practices
Module 3: AWS Bedrock
Foundation model management
Provisioned throughput configuration
Prompt engineering and evaluation
RAG implementation with Bedrock
Module 4: SageMaker Canvas and MLOps
No-code ML development with SageMaker Canvas
Data preparation and wrangling
Model development and deployment
Course conclusion and best practices
Key Technologies Covered
Amazon Q Developer
AWS Bedrock
SageMaker Canvas
Foundation Models
RAG (Retrieval Augmented Generation)
MLOps Tools
Vector Databases
AWS Lambda
Amazon OpenSearch
AWS S3