Amazon Web Services

In this comprehensive video, AWS generative AI expert Emily Webber demonstrates how to prepare data and train at scale using Amazon Web Services. She covers multiple options for data preparation, including S3 buckets, ECR images, FSx for Lustre, and SageMaker. Webber explains how to set up distributed file systems, use SageMaker warm pools for efficient development, and scale up training runs. The video includes a hands-on walkthrough of creating SageMaker warm pools and running them with FSx for Lustre, as well as troubleshooting tips for large-scale distributed training. Viewers will learn how to optimize their workflow for training foundation models and generative AI systems on AWS infrastructure.

product-information
skills-and-how-to
generative-ai
ai-ml
gen-ai
Show 7 more

Up Next

VideoThumbnail
30:02

Builders 온라인 시리즈 | Amazon VPC와 온프레미스 네트워크 연결하기

Jun 27, 2025
VideoThumbnail
26:52

Builders 온라인 시리즈 | 당신의 아키텍처는 Well-Architected 한가요?

Jun 27, 2025
VideoThumbnail
28:50

완전관리형 컨테이너 서비스 Amazon ECS로 애플리케이션 쉽게 구축하기 - AWS TechCamp

Jun 26, 2025
VideoThumbnail
18:39

기초부터 배우는 AWS 핵심 서비스로 웹 애플리케이션 구축하기 - AWS TechCamp

Jun 26, 2025
VideoThumbnail
18:56

Amazon Bedrock을 활용하여 상품리뷰 요약과 비디오 숏폼 만들기 - AWS TechCamp

Jun 26, 2025