The course provides an overview of generative AI, planning a generative AI project, getting started with Amazon Bedrock, the foundations of prompt engineering, and the architecture patterns to build generative AI applications using Amazon Bedrock and LangChain.
Day 1
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
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
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
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
Day 2
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
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
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
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