Praktische Tutorials

Set up an AWS Transfer Family web app to enable a simple interface for transferring data to and from Amazon S3 via a web browser.

Learn how to utilize Amazon Bedrock and Amazon Textract to extract and process information from unstructured documents.

Learn how to deploy a sample containerized application on a Nginx server using AWS App Runner.

Learn how to build and deploy a React web application with user authentication, a database, and storage using AWS Amplify.

Learn how to use AWS Amplify to build a serverless web application powered by Generative AI using Amazon Bedrock and the Claude 3 Sonnet foundation model.

Learn how to host your personal or simple marketing website on AWS.

Learn how to deploy a web application with AWS Amplify.

Learn how to build and host a full-stack React app with AWS Amplify, featuring authentication, data, and serverless functions.

Learn how to configure and connect to Amazon Aurora Serverless v2.

Learn how to send your first email using Amazon SES.

Learn how to use Amazon SageMaker Canvas to build machine learning (ML) models and generate accurate predictions without writing a single line of code.

Learn how to set up your AWS account and development environment. This will allow you to interact with your AWS account and provision any resources you need for building a system programmatically.

Learn to build a continuous delivery pipeline for a simple web application using AWS CodeBuild and AWS CodePipeline.

Learn how to replicate objects already existing in your buckets within the same AWS Region or across different AWS Regions with Amazon Simple Storage Service (Amazon S3) Batch Replication.

In this tutorial, you learn and experiment with machine learning using Amazon SageMaker Studio Lab, a no-setup, free development environment.

In this tutorial, you’ll learn how to use Amazon SageMaker to train, a machine learning (ML) model using the AWS Trainium instances.

Learn how to publish a .NET application on a Windows Server 2022 instance in Amazon Lightsail.

Learn how to use Amazon SageMaker geospatial capabilities to access readily available geospatial data, make ML predictions, and visualize the results.