This course is designed to introduce generative AI to software developers interested in leveraging large language models without fine-tuning. 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.
Course Objectives
In this course, you will learn to:
- Define the importance of generative AI and explain its potential risks and benefits.
- Discuss the technical foundations and key terminology for generative AI.
- Recognize the benefits and use cases of Amazon Bedrock.
- Describe the basic functions, types, and various use cases of foundation models.
- Define prompt engineering and apply general best practices when interacting with FMs.
- Describe Amazon Bedrock foundation models, inference parameters, and key Amazon Bedrock APIs.
- Describe architecture patterns that can be implemented with Amazon Bedrock for building useful generative AI
applications. - Describe how to integrate LangChain with large language models (LLMs), prompt templates, chains, chat models, text embeddings models, document loaders, retrievers, and Agents for Amazon Bedrock.
- Build and test several examples of use cases that employ various Amazon Bedrock models, LangChain, and the Retrieval Augmented Generation (RAG) approach.
Intended Audience
This course is intended for:
- Software developers interested in leveraging large language models without fine-tuning
Prerequisites
We recommend that attendees of this course have the following prerequisites:
- Completed AWS Technical Essentials
- Intermediate-level proficiency in Python
Outline
Course Welcome
Module 1 – Introduction to Generative AI – Art of the Possible
Module 2 – Planning a Generative AI Project
Module 3 – Getting Started with Amazon Bedrock
Module 4 – Foundations of Prompt Engineering
Module 5 – Amazon Bedrock Application Components
Module 6 – Amazon Bedrock Foundation Models
Module 7 – LangChain
Module 8 – Architecture Patterns
Course Summary and Resources
