AWS App Studio is a generative AI-powered service that uses natural language to create enterprise-grade applications. App Studio opens up application development to technical professionals without software development skills, such as IT project managers, data engineers, and enterprise architects, empowering them to quickly build applications that are secure and fully managed by AWS, eliminating the need for operational expertise.

In this workshop, you will build a sample generative AI document chatbot app on AWS using Amazon Bedrock and Generative AI Terraform Modules. You will learn the common infrastructure patterns for generative AI apps on AWS, and take advantage of Terraform to easily deploy the required architecture while avoiding the undifferentiated heavy lifting of reinventing common architectural patterns from scratch.

Throughout this workshop, you'll learn how to leverage Guardrails for Amazon Bedrock to consistently apply AI safety measures across your applications, including blocking undesirable topics, filtering harmful content, redacting sensitive information, and detecting hallucinations through contextual grounding checks. By the end of this workshop, you'll have gained hands-on experience in configuring and applying Guardrails to align your generative AI applications with your organization's responsible AI policies.

Ensuring security is a critical priority when developing and deploying generative AI applications for sensitive use cases. By prioritizing security from the initial design phase through development, testing, and eventual deployment of AI-ML systems, misuse can be prevented while still enabling innovation. This session aims to equip customers with techniques to make their machine learning workflows more secure, using familiar security controls. Overall, building security considerations into every stage of ML development and deployment allows for responsible AI innovation.

This workshop gives you hands-on experience working with Agents for Amazon Bedrock, the easiest way to create Generative AI applications. It provides examples of how to connect with existent APIs and Knowledge Bases. It cover various topics from action group definition with Lambda execution or Return of Control, Knowledge Bases Integration, Session State definition and Advanced Prompts.

This workshop gives you hands-on experience on Amazon Bedrock, the easiest way to build and scale generative AI applications with foundation models. It provides examples for prompt engineering, text generation, Knowledge Bases for Amazon Bedrock and RAG, model customization, image and multi-modal applications, Agents for Amazon Bedrock and Open source integration with Amazon Bedrock.

In this workshop, you will build a sample generative AI document chatbot app on AWS using Amazon Bedrock and Generative AI CDK Constructs. You will learn the common infrastructure patterns for generative AI apps on AWS, and take advantage of the AWS CDK (Cloud Development Kit) to easily deploy the required architecture while avoiding the undifferentiated heavy lifting of reinventing common architectural patterns from scratch.

This workshop focuses on accelerating Advertising and Marketing Industry usecases by applying AWS Generative AI and Machine Learning services. The workshop has modules focusing on - Advertising Moodboard Generation using AIML services - Ad Copy Generation using AIML services

In this workshop, participants will gain insights into the RAG technique and acquire the skills to construct a chatbot. This chatbot allows users to pose questions, bot utilizing a Foundation Model (FM) using Amazon Bedrock, responds based on pre-indexed content with choice of large language model (LLM). Amazon Bedrock is a fully managed service, offering access to foundation models from Amazon and leading AI startups through an API. This allows users to select from a range of FMs, tailoring the model to their specific use case. For the storage, indexing, and retrieval of content, the workshop incorporates Amazon Kendra an intelligent enterprise search service powered by machine learning. To execute the application code in an event-driven manner, AWS Lambda is employed as the serverless compute. Lastly, the solution integrates the LangChain agent to orchestrate the RAG flow.

This workshop enables participants to build simple generative AI demo applications while learning key concepts. Labs include chatbots, retrieval-augmented generation, image generation, document summarization, data extraction, streaming responses, and prompt engineering. User interfaces are built using Streamlit. The labs are designed for builders with no previous data science experience. To run this workshop, you'll need access to an AWS account with Bedrock activated.