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Hands-on AWS lab for reducing compute costs and resource use through scheduling, right-sizing, and Graviton processor migrations.
Build and extend a gated AWS CI/CD pipeline that tests a containerized application, provisions environments with AWS CDK, and delivers it through test and production stages.
Hands-on lab using Amazon Q Developer in Visual Studio Code to explain, generate, fix, optimize, and enhance application code.
Build a loan-portfolio dashboard in Amazon QuickSight using Generative BI to create visualizations, executive summaries, and data stories for decision support.
Hands-on lab using Amazon Bedrock and LangChain to generate and summarize text, answer questions, build a chatbot, and generate code.
Introducción práctica a Amazon Comprehend con laboratorios de clasificación personalizada y reconocimiento de entidades personalizadas.
Laboratório prático para configurar endpoints da VPC e restringir o acesso a buckets do S3, com versionamento e restauração de objetos excluídos.
Laboratorio práctico para crear, montar y supervisar un sistema de archivos de Amazon EFS desde la consola de AWS y una instancia Linux.
AWS 기반 LLMOps 참조 아키텍처를 통해 LLM 애플리케이션의 개발, 배포, 평가 및 운영을 살펴봅니다.
Amazon SageMaker JumpStartの基盤モデルとSageMaker Canvasを使い、AWSで生成AIアプリケーションを構築する方法を学びます。
面向游戏开发者,学习在 AWS 云中设计游戏后端、分析管道、监控方案并管理基础设施成本。
Panduan menggunakan Amazon Q Developer untuk meningkatkan produktivitas developer dan membangun aplikasi di AWS sepanjang siklus hidup pengembangan perangkat lunak.
Pengantar machine learning berbasis kasus penggunaan, dengan demonstrasi Amazon SageMaker Canvas untuk membangun, melatih, dan menerapkan model tanpa kode.
Laboratório prático de configuração do Elastic Load Balancing para distribuir tráfego entre instâncias Amazon EC2 e observar suas métricas.
Laboratório prático para usar o Amazon Inspector em auditorias de rede e host, investigar vulnerabilidades e automatizar o envio de descobertas na AWS.
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