With Amazon Managed Streaming for Apache Kafka (Amazon MSK), you can build and run applications that use Apache Kafka to process real-time data streams. In this course, you will learn the benefits and technical concepts of Amazon MSK. If you are new to the service, you will learn how to start using Amazon MSK through a demonstration using the AWS Management Console. You will learn about using a fully managed service to simplify the process of building and running Apache Kafka clusters, eliminating the need to manage infrastructure.

With Amazon Managed Workflows for Apache Airflow (Amazon MWAA), you can build, schedule, and monitor complex data pipelines and workflows without managing the underlying infrastructure. In this course, you will learn the benefits and technical concepts of Amazon MWAA. If you are new to the service, you will learn how to start using Amazon MWAA through a demonstration using the AWS Management Console. You will learn how Amazon MWAA can streamline data processing tasks, automate repetitive operations, and orchestrate multi-step workflows.

With Amazon MQ, you can create message queues and topics, which organize and distribute messages differently. In this course, you will learn the benefits and technical concepts of Amazon MQ. If you are new to the service, you will learn how to start using Amazon MQ through a demonstration using the AWS Management Console. You will learn about how Amazon MQ enables applications and services to communicate and exchange data, even when running on different systems or platforms.

With Amazon Polly, you can convert written text into natural human-like speech allowing applications to speak with natural-sounding voices.

Amazon Q Business is generative artificial intelligence (generative AI) powered assistant that can answer questions, generate content, create summaries, and complete tasks—all based on the information in your enterprise.

Amazon Q Developer is a generative artificial intelligence (AI) powered assistant that helps you understand, build, extend, and operate AWS applications throughout the software development lifecycle. In this Getting Started course, you will learn about the benefits, features, typical use cases, technical concepts, and cost of using Amazon Q Developer. You will review an architecture that uses Amazon Q Developer in interactive and asynchronous environments to chat with applications and customize and transform code. Through a guided tutorial consisting of a narrated video, step-by-step instructions and transcript, you will learn how to setup an interactive development environment (IDE) that uses Amazon Q Developer. You will use that environment to optimize code, transform code written in Java 8 to Java 17, and implement a new feature in a project.

Amazon QuickSight is a cloud-scale business intelligence (BI) service that you can use to create and publish interactive dashboards. You can access these from browsers or mobile devices. As a fully managed cloud-based service, QuickSight combines data from many different sources and provides user management tools that you can use to scale from a few users to millions. In this course, you will learn about the benefits and technical concepts of QuickSight. You will learn about the architecture and built-in features. You will have an opportunity to try key features through demonstrations.

In this course, you will learn the benefits and technical concepts of Amazon RDS for MySQL. If you are new to the service, you will learn how to start using Amazon RDS for MySQL through a demonstration using the AWS Management Console. You will learn about how Amazon RDS for MySQL eliminates the need for manual database management, reducing operational overhead and enabling you to focus on application development.

In this course, you will learn the benefits and technical concepts of Amazon RDS for Oracle. If you are new to the service, you will learn how to start using Amazon RDS for Oracle through a demonstration using the AWS Management Console. You will learn about offloading time-consuming database administration tasks to AWS, so you can focus on your applications and business logic.

In this course, you will learn the benefits and technical concepts of RDS for SQL Server. You will learn about how RDS for SQL Server automates time-consuming database administration tasks so you can focus on your applications and business logic. If you are new to the service, you will learn how to start using RDS for SQL Server through a demonstration using the AWS Management Console.

In this course, you will learn the benefits, typical use cases, and technical concepts of Amazon Redshift. You can also try the service through a demonstration using the AWS Management Console. The cloud data warehouse service integrates with data lakes based on Amazon Simple Storage Service (Amazon S3). It also integrates with relational database services such as Amazon Relational Database Service (Amazon RDS) for PostgreSQL, Amazon Aurora PostgreSQL-Compatible Edition, Amazon RDS for MySQL, and Amazon Aurora MySQL-Compatible Edition. Amazon Redshift supports building and using machine learning (ML) models using familiar SQL commands, thereby reducing the skills needed to take advantage of ML.

With Amazon Route 53, you can translate human-readable domain names into IP addresses that computers use to identify each other. In this course, you will learn the benefits and technical concepts of Route 53. If you are new to the service, you will learn how to start using Route 53 through a demonstration that uses the AWS Management Console. You will learn about how this powerful service solves common networking challenges, offers unique benefits, and integrates into your overall Amazon Web Services (AWS) infrastructure strategy.

With Amazon Simple Storage Service (Amazon S3), you can store and retrieve any amount of data from anywhere on the web. In this course, you will learn the benefits and technical concepts of Amazon S3. If you are new to the service, you will learn how to start using Amazon S3 through a demonstration using the AWS Management Console. You will learn about how Amazon S3 provides highly reliable, infinitely expandable cloud storage that eliminates the need to manage physical infrastructure.

Amazon S3 Vectors helps you create AI-powered search and similarity matching in Amazon Simple Storage Service (Amazon S3). This enables semantic search, recommendation systems, and similarity matching across documents, images, and other content types. You can maintain security and cost efficiency while building modern AI applications. Learn how to effectively use S3 Vectors to build vector storage solutions that optimize semantic search and AI applications.

In this course, you will learn the benefits and technical concepts of Amazon SageMaker AI. If you are new to the service, you will learn how to start using Amazon SageMaker AI through a demonstration using the AWS Management Console. You will use a Jupyter notebook instance to train and generate prediction using a machine learning model.

Amazon Transcribe is a fully managed artificial intelligence (AI) service that helps you convert speech to text using automatic speech recognition (ASR) technology.

Amazon WorkSpaces is a managed service that streamlines desktop delivery in the cloud. It provides secure Windows or Linux desktops that users can access from anywhere with an internet connection. Amazon WorkSpaces eliminates the complexity of managing traditional desktop infrastructure while giving users the desktop experience they need to be productive. Learn how to effectively use Amazon WorkSpaces to build secure and flexible virtual desktop solutions.

This is an introduction to the various analytics services in Amazon Web Services (AWS).

This is an introduction to the various application integration services in Amazon Web Services (AWS).

In this course, you will learn key concepts, basic architecture, and implementation approaches for AWS Application Migration Service (AWS MGN). A step-by-step walk-through guides you through the entire process of performing a migration with AWS MGN. This training is recommended if you are actively working on migration projects with the service or are assisting customers in doing so.