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AWS Skill Builder is an Amazon-hosted platform for developers to create, manage and deploy Alexa skills. It provides a range of resources and tools to help you build your skills quickly and easily.
Pelajari strategi keberlanjutan untuk mengoptimalkan beban kerja AI Generatif di AWS, dengan fokus pada pengurangan jejak karbon dan efisiensi penggunaan sumber daya komputasi.
Discover how to minimize carbon footprints in generative AI workloads through AWS Well-Architected Framework's sustainability principles, focusing on computing and data management strategies.
生成AIワークロードの二酸化炭素排出量を削減するため、AWS Well-Architectedフレームワークを活用した持続可能性戦略とベストプラクティスを習得します。
Delve into container-based application deployment on AWS, from basic concepts to advanced implementations using ECS, Fargate, and AWS Copilot, with hands-on demos and integration practices.
Delve into konsep dasar DevOps, manfaat implementasinya, serta praktik Infrastructure as Code dan CI/CD pipeline untuk meningkatkan efisiensi pengembangan aplikasi di AWS.
Delve into responsible AI principles, covering ethics, fairness, privacy, and governance while learning practical implementation strategies using AWS tools and services for generative AI development.
掌握生成式AI工作负载的可持续发展策略,优化资源利用率,减少碳足迹,并通过AWS Well-Architected Framework实现环保效益最大化。
Discover how to protect against ransomware using AWS security services, from basic principles to practical implementation based on NIST framework and AWS Well-Architected best practices. (159 characters)
Delve into building generative AI applications on AWS using Amazon SageMaker Jumpstart and Canvas, with practical demos and fundamental concepts explained in Bahasa Indonesia with English narration.
Delve into operationalizing LLM applications with comprehensive coverage of deployment, evaluation, fine-tuning, monitoring, and governance practices in AWS environment using RAG and PEFT techniques.
Discover 機械学習システム構築の基礎、前処理から評価まで包括的に学び、外れ値、ハイパーパラメータ、F1スコアなど重要な概念を実践的なデータで理解する90分の入門講座。
Dive into LLMOps with AWS, mastering production-ready generative AI applications through comprehensive architecture, evaluation methods, RAG implementation, fine-tuning techniques, and security best practices.
Discover AWS의 생성형 AI 애플리케이션 구축 옵션과 Amazon SageMaker JumpStart의 파운데이션 모델을 활용한 실용적인 구현 방법을 통해 AI 개발 역량을 강화하세요.
Dive into 확산 모델의 개념과 실제 적용을 통해 이미지 생성 AI의 비즈니스 가치를 파악하고, Stable Diffusion과 Amazon Bedrock을 활용한 실무 구현 방법을 습득하세요.
Discover how to build generative AI applications on AWS using SageMaker JumpStart, Bedrock, and Canvas - from foundational concepts to practical implementations for both developers and analysts.
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