Workshops

SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing machine learning (ML) infrastructure for training foundation models (FMs), reducing training time by up to 40%. In this builders’ session, learn how to pre-train a large language model (LLM) using Slurm on SageMaker HyperPod. Explore the model pre-training workflow from start to finish, including setting up clusters, troubleshooting convergence issues, and running distributed training.

This workshop provides hands-on experience in cloud computing basics, containers, High Performance Computing (HPC), and AI/Machine Learning for researchers and research IT staff with little to no cloud computing background.

This hands-on workshop demonstrates how to implement real-time data processing using AWS data streaming services, combining Apache Kafka (MSK), Apache Flink (MSF), and Amazon Bedrock for Agentic AI integration.

This entry-level workshop is designed for individuals who are new to Amazon Web Services and want to gain practical experience in setting up and storing data in our variety of NoSQL database services.

In this workshop, discover how to build a complete coffee-ordering serverless web application. Learn about event-driven architectures and how to use services such as AWS Lambda, Amazon EventBridge, AWS Lambda Durable Functions, and more. Create a scalable, serverless web application that allows users to order coffee and baristas to keep track of and fulfill orders.

In this workshop, learn how to get started with Large Language Model (LLM) applications and inference on Amazon EKS. Discover how to deploy and manage production-grade LLM workloads. Through hands-on labs, you'll explore how to leverage Amazon EKS along with AWS services and open-source tools to create robust LLM solutions. The workshop environment provides all the necessary infrastructure and tools, allowing you to focus on learning and implementation.

This workshop is focused on Rehosting and Tagging activities. It enables participants to perform a complete migration to AWS supported by AWS Application Migration Service. It also offers a tagging playground using different automation methods. This workshop is part of a series, check the “Migration and Modernization Pathways – Lab2” and “Migration and Modernization Pathways – Lab3” for learning about the different modernization pathways.

The Migration and Modernization Pathways – Lab Day 2 is designed for technical audiences exploring the different pathways, including: Move to Modern DevOps, Move to AI, and Move to Containers. This workshop is part of a series, check the “Migration and Modernization Pathways – Lab 3” for other pathways and the "Migration and Modernization - Rehost and Tagging - Lab 1" for Application Migration Service and tagging.

A new version of this workshop has been published on Aug 6. Basic knowledge of AgentCore fundamentals is a prerequisite. Please complete the pre-work of pre-testing the workshop and identifying the right subset of samples for your audience. Use the materials in the workshop studio - videos, blogs and reading material to prepare before delivering or attending the workshop. Claude Code is configured with AWS documentation MCP servers as your learning partner.

Discover how to effectively implement generative AI in your business operations using Amazon Bedrock with Langfuse on AWS. While many organizations are enthusiastic about large language models (LLMs), successful integration into daily operations requires strategic planning and proper implementation.