Developing Generative AI Applications on AWS (DGAIA) – Outline

Detailed Course Outline

Module 1: Introduction to Generative AI – Art of the Possible
  • Overview of ML
  • Basics of generative AI
  • Generative AI use cases
  • Generative AI in practice
  • Risks and benefits
Module 2: Planning a Generative AI Project
  • Generative AI fundamentals
  • Generative AI in practice
  • Generative AI context
  • Steps in planning a generative AI project
  • Risks and mitigation
Module 3: Getting Started with Amazon Bedrock
  • Introduction to Amazon Bedrock
  • Architecture and use cases
  • How to use Amazon Bedrock
  • Demonstration: Setting up Bedrock access and using playgrounds
Module 4: Foundations of Prompt Engineering
  • Basics of foundation models
  • Fundamentals of prompt engineering
  • Basic prompt techniques
  • Advanced prompt techniques
  • Model-specific prompt techniques
  • Demonstration: Fine-tuning a basic text prompt
  • Addressing prompt misuses
  • Mitigating bias
  • Demonstration: Image bias mitigation
Module 5: Amazon Bedrock Application Components
  • Overview of generative AI application components
  • Foundation models and the FM interface
  • Working with datasets and embeddings
  • Demonstration: Word embeddings
  • Additional application components
  • Retrieval Augmented Generation (RAG)
  • Model fine-tuning
  • Securing generative AI applications
  • Generative AI application architecture
Module 6: Amazon Bedrock Foundation Models
  • Introduction to Amazon Bedrock foundation models
  • Using Amazon Bedrock FMs for inference
  • Amazon Bedrock methods
  • Data protection and auditability
  • Demonstration: Invoke Bedrock model for text generation using zero-shot prompt
Module 7: LangChain
  • Optimizing LLM performance
  • Using models with LangChain
  • Constructing prompts
  • Demonstration: Bedrock with LangChain using a prompt that includes context
  • Structuring documents with indexes
  • Storing and retrieving data with memory
  • Using chains to sequence components
  • Managing external resources with LangChain agents
Module 8: Architecture Patterns
  • Introduction to architecture patterns
  • Text summarization
  • Demonstration: Text summarization of small files with Anthropic Claude
  • Demonstration: Abstractive text summarization with Amazon Titan using LangChain
  • Question answering
  • Demonstration: Using Amazon Bedrock for question answering
  • Chatbot
  • Demonstration: Conversational interface – Chatbot with AI21 LLM
  • Code generation
  • Demonstration: Using Amazon Bedrock models for code generation
  • LangChain and agents for Amazon Bedrock
  • Demonstration: Integrating Amazon Bedrock models with LangChain agents