Developing Generative AI Applications on AWS

SKU: AMWSGAIA

386.280 kr.

This two-day advanced course is designed for software developers seeking to leverage large language models (LLMs) without fine-tuning, using Amazon Bedrock and LangChain. It covers the basics of generative AI, the foundations of prompt engineering, and architecture patterns for building generative AI applications.

Forkröfur

  • Completion of AWS Technical Essentials
  • Intermediate proficiency in Python

Target Audience

This course is intended for software developers who:

  • Want to integrate generative AI models into their applications
  • Are interested in Amazon Bedrock and LangChain for generative AI use cases

Nemandi mun læra eftirfarandi

By the end of this course, you will be able to:

  • Describe generative AI and its alignment with machine learning
  • Identify the business value of generative AI use cases
  • Plan and mitigate risks in generative AI projects
  • Understand and implement Amazon Bedrock for generative AI applications
  • Apply prompt engineering techniques
  • Build and secure generative AI applications using Amazon Bedrock and LangChain
  • Design and implement architecture patterns for various generative AI use cases

Samantekt

Day One
Module 1: Introduction to Generative AI – Art of the Possible

  • Overview of machine learning
  • Generative AI use cases
  • Risks and benefits of generative AI

Module 2: Planning a Generative AI Project

  • Steps in planning
  • Identifying risks and mitigation strategies

Module 3: Getting Started with Amazon Bedrock

  • Introduction to Amazon Bedrock
  • Setting up and using Bedrock in the AWS Console
  • Hands-on demonstration

Module 4: Foundations of Prompt Engineering

  • Basics of prompt engineering
  • Advanced techniques and addressing prompt misuse
  • Mitigating bias in prompts
  • Hands-on demonstration: Prompt fine-tuning and bias mitigation

Day Two
Module 5: Amazon Bedrock Application Components

  • Overview of application components (e.g., datasets, embeddings)
  • Introduction to RAG (Retrieval Augmented Generation)
  • Securing applications

Module 6: Amazon Bedrock Foundation Models

  • Amazon Bedrock models and methods
  • Hands-on lab: Zero-shot text generation

Module 7: LangChain

  • Integrating AWS with LangChain
  • Using LangChain agents for prompt templates, chat models, and document loaders
  • Hands-on lab: Building applications with LangChain

Module 8: Architecture Patterns

  • Generative AI architecture patterns
  • Hands-on labs: Text summarisation, chatbots, question answering, and code generation using Amazon Bedrock and LangChain