AWS Training—always flexible, always on demand

Flexibility to learn your way

Whether you’re exploring new ideas or sharpening your cloud skills, AWS Training can help you reach your goals faster. Learn at your own pace with hundreds of free on-demand courses and progress from foundational to intermediate- and advanced-level training. For hands-on learning, register for virtual instructor-led classroom training and get on-the-spot practical help.

Advance your career

The supply of IT professionals with the right cloud skills is not keeping pace with demand. Investing your time in cloud education now can help you take advantage of this opportunity. Acquire in-demand cloud expertise to give yourself a competitive advantage and grow your career.

Build AWS Cloud skills for success

  • Digital Training

    Choose from 500+ free, on-demand digital courses to build your AWS Cloud knowledge and skills. Our portfolio covers AWS services and solutions, from machine learning, to networking, security and more - designed for all skill levels.

  • Public Training Events

    Join AWS experts at both virtual and on-demand events. Connect and collaborate with your peers in the AWS Cloud community. Gain new skills and discover how to leverage AWS products and solutions.

  • Digital Training Partners

    Find AWS self-paced courses covering a range of topics from AWS Cloud fundamentals to machine learning at top online learning platforms including Coursera, edX, Trailhead and Udacity.

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AWS Power Hour: Architecting


Join us for our fun, free, and interactive Twitch series, AWS Power Hour: Architecting, to learn the essential information you need to build your future in the AWS Cloud. Whether you simply want to better understand architecting or you’re participating in the Get AWS Certified: Solutions Architect Challenge, our hosts will guide you through the content with demonstrations and real-world examples.

Interactive cloud learning with Twitch

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Build AWS Cloud skills for success

  • AWS Cloud Practitioner Essentials

    Foundational | 6 hours

    In this self-paced digital course, you’ll gain an overall understanding of AWS Cloud, independent of specific technical roles. It provides a detailed overview of cloud concepts, AWS services, security, architecture, pricing, and support. This course also helps you prepare for the AWS Certified Cloud Practitioner exam.

  • Introduction to Amazon Elastic Compute Cloud

    Foundational | 10 minutes

    This is an introduction to Amazon Elastic Compute Cloud (Amazon EC2), a web service that provides secure, resizable compute capacity in the cloud. In this course, we provide an overview of the service and demonstrate how to build and configure an Amazon EC2 instance.

  • AWS Security Fundamentals (Second Edition)

    Foundational | 2 hours

    Learn fundamental AWS cloud security concepts, including AWS access control, data encryption methods, and how network access to your AWS infrastructure can be secured. This self-paced course will address your security responsibility in the AWS cloud and the different security- oriented services available.

Choose your learning path

Learning paths are the progressions of courses and exams we recommend you follow to help advance your skills or prepare you to use the AWS Cloud.

  • Cloud Practitioner

    This learning path is intended for individuals who are looking to learn cloud fundamentals and best practices.

  • Architect

    This learning path is designed for solutions architects, solution design engineers, and anyone who wants to learn how to design highly available systems on AWS.

  • DevOps Engineer

    This learning path is designed for individuals who want to learn how to use the most common DevOps patterns to design, deploy and manage AWS Cloud systems.

  • All Learning Paths

    Explore our learning paths grouped by role, solutions area, or your APN Partner needs.

Explore AWS Partner options

  • AWS PartnerCast

    This weekly series of free interactive webinars explores how AWS products and services can help AWS Partners in business and technical roles create new client opportunities, build professional relationships, and develop AWS Cloud skills.

  • Partner Learning Guide

    Download this guide for information on online training and certification resources designed for AWS Partners. You can build your AWS Cloud skills using our free, self-paced digital courses and virtual classroom training, all created by AWS experts.

  • Online Learning for AWS Partners

    Browse virtual and digital offerings to support your AWS Partner training, certification, and accreditation goals.


Register for SageMaker Fridays



Boost ML development productivity with managed SageMaker notebooks

Amazon SageMaker offers fully managed SageMaker Studio notebooks and notebook instances for data exploration and building ML models. Introducing next generation SageMaker notebooks to help ML practitioners scale end-to-end ML development more efficiently. Join this session to learn how to increase productivity with the new notebook capabilities, from simplifying data preparation, to collaborating in real time and automatically converting notebook code to production-ready jobs.

Who should attend: Data Scientists, Data Engineers, ML Developers, ML Engineers

Date: On-demand

60-minute episode: Watch now ›

Improve governance of your ML projects with Amazon SageMaker

As companies are increasingly adopting ML in mainstream enterprise applications, they require control over and visibility into their ML projects, also known as ML governance. Amazon SageMaker recently launched new capabilities to help customers define user permissions, and create a single source of truth for model information and gain insights into model performance and troubleshoot deviations from a single view. Join us for a deep dive into Amazon SageMaker Role Manager, SageMaker Model Cards, and SageMaker Model Dashboard.

Who should attend: Data Scientists, Developers, ML Practitioners, ML Platform Administrators, ML Administrators, ML Risk and Compliance Officers

Date: On-demand

60-minute episodeWatch now ›

15-minute snack: What is ML governance? | Watch now on AWS ML LinkedIn ›

Easily build, train, and deploy ML models using geospatial data

Today, the majority of all data generated contains geospatial information, but only a small fraction of it is used for ML because accessing, processing, and visualizing the data is complex, time consuming, and expensive. With Amazon SageMaker’s new geospatial capabilities, you can access readily available geospatial data sources, easily process large-scale geospatial datasets with purpose-built operations, accelerate model building with pretrained ML models, and use rich visualization tools to explore predictions on an interactive map. Join us for an interactive demo and learn how to make faster and smarter decisions using the power of geospatial data.

Who should attend: Data Scientists, Data Engineers, ML Developers, ML Engineers

DateMarch 31st, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episode: Watch now ›

15-minute snack: Why geospatial ML? | Watch now on AWS ML LinkedIn ›

Use Amazon SageMaker to build generative AI applications

Tune in to learn how to fine-tune and deploy large language and vision models on Amazon SageMaker to build your generative AI applications. We will explore popular generative AI use cases such as image generation, search, chat, and document summarization. Join our experts for a deep dive conversation and interactive demo.

Who should attend: Data Scientists, Data Engineers, ML Developers, ML Engineers

Date: April 28th, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episodeWatch now ›

15-minute snack: Preparing data at scale with Amazon SageMaker notebooks | Watch now ›

No-code ML for faster decision making

Organizations everywhere use ML to accurately predict outcomes and make faster business decisions. However, this often requires preparing, building, training, and deploying ML models. With Amazon SageMaker Canvas, non-technical business users can generate accurate ML predictions on their own without requiring any ML experience or writing a single line of code. In this session, you'll learn how you can use SageMaker Canvas to connect, prepare, analyze, and explore data, automatically build ML models, and collaborate with data scientists to increase productivity. You'll even learn how you can import ML models from anywhere and generate predictions directly in Amazon SageMaker Canvas.

Who should attend: Data Scientists, Business Analysts, Data Scientists, Line of business leads

Date: May 26th, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episode: Watch now ›

15-minute snack: Managing ML experiments | Watch now ›

Deploying machine learning models for inference

Maximizing inference performance while reducing cost is critical to delivering great customer experiences through ML. Amazon SageMaker provides a breadth and depth of fully managed deployment features to achieve optimal inference performance and cost at scale without the operational burden. In this episode, learn how to use SageMaker inference capabilities to quickly deploy ML models in production for any use case, including hyper-personalization, Generative AI, and Large Language Models (LLMs).

Who should attend: Data Scientists, ML Engineers

Date: June 30th, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episode: Watch now ›

15-minute snack: A journey from beginning to advanced ML builder | Watch now on AWS ML LinkedIn ›

Deliver high-performance ML models faster with MLOps tools

Machine learning operations (MLOps) tools help you automate and standardize the ML lifecycle to productionize ML models faster without compromising model performance. Amazon SageMaker provides a breadth of mission-ready MLOps tools to experiment, train, test, deploy, and govern ML models at scale. In this session, learn how to use SageMaker to implement an end-to-end MLOps solution for your organization.

Who should attend: ML Engineers, Data Scientists, Data Engineers

Date: July 28th, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episode: Watch now ›

15-minute snack: Train your ML models at scale | Watch now ›

Accelerate your ML journey with Amazon SageMaker low-code ML tools

The machine learning (ML) journey requires continuous experimentation and rapid prototyping to be successful. In order to create highly accurate models, data scientists have to first experiment with feature engineering, model selection, and optimization techniques, which can be time-consuming and expensive. In this session, learn how low-code ML tools, including Amazon SageMaker Data Wrangler, Amazon SageMaker Autopilot, and Amazon SageMaker JumpStart, make it easier to experiment faster and bring highly accurate models to production more quickly and efficiently.

Who should attend: Data Scientists, Data Engineers, ML Developers, ML Engineers

Date: August 25th, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episode: Watch now ›

15-minute snack: Generative AI on AWS | Watch now ›

Prepare ML data faster and at scale with Amazon SageMaker

Data preparation for ML is a difficult process. It requires extracting and normalizing data and performing feature engineering, which can be time consuming. With Amazon SageMaker you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, bias detection, and visualization from a single visual interface. In this session, you'll learn how you can use Amazon SageMaker to reduce the time it takes to aggregate and prepare structured data for ML from weeks to minutes.

Who should attend: Data Scientists, Data Engineers

Date: September 29th, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episode: Register now ›

15-minute snack: Amazon SageMaker high-performance inference at low cost | Watch now on AWS ML LinkedIn ›

Build high performance, energy-efficient, and cost-effective ML applications with Amazon SageMaker, AWS Trainium, and AWS Inferentia

Managing the underlying infrastructure while building, training, and deploying machine learning (ML) models at scale can be technically intensive without the right tools and expertise. Amazon SageMaker is a fully managed ML service to build, train, and deploy ML models so you can focus on ML innovation instead of tedious infrastructure management. SageMaker offers you a choice of high-performance ML accelerators such as AWS Trainium and AWS Inferentia which are purpose-built for large-scale models such as LLMs and deliver 50% lower cost-to-train and 70% lower cost per inference. In this session, learn how you can build your own generative AI applications using Amazon SageMaker, AWS Trainium, and AWS Inferentia. In addition, we will also share how you can get started by using self-managed services such as AWS Deep Learning Container, AWS Deep learning AMIs, and ML frameworks and model libraries such as TensorFlow, PyTorch and Hugging Face.

Who should attend: Data Scientists, ML Developers, and ML Engineers

Date: October 27th, 2023 | 9:00 AM PT | 12:00 PM ET

60-minute episode: Register now ›

15-minute snacks: Coming soon | June 2nd, June 9th, and October 20th on AWS ML LinkedIn ›