Course Content
Developing Generative AI Solutions on AWS
    About Lesson

    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 Finetuning 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 finetuning  
    • 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 zeroshot 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