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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.
Build and optimize secure streaming data pipelines on AWS with hands-on labs using Amazon Kinesis, Amazon MSK, and Managed Apache Flink.
AI、機械学習、生成AIが各業界のビジネス課題にどう活用され、いつ適さないかを学ぶ入門コース。
生成AI搭載アシスタントAmazon Qの目的、用途、安全かつ確実な生産性向上の可能性を紹介します。
生成AIアプリケーションのライフサイクルを通じて、基盤モデルの選択・カスタマイズ・評価・デプロイの基本を学びます。
Build and optimize a secure, scalable AWS data lake through guided architecture lessons and hands-on labs with Amazon S3 and Lake Formation.
Overview of AWS options for building generative AI applications with foundation models in Amazon SageMaker JumpStart, Bedrock, and SageMaker Canvas.
An introduction to responsible AI for generative AI, covering fairness, explainability, privacy, robustness, governance, transparency, and AWS tools.
Explore diffusion models for image generation, compare them with GANs, evaluate their use cases, and fine-tune pretrained models for specific tasks.
Explore real-world generative AI use cases that improve customer experience, employee productivity, business processes, and creative work across industries.
Overview of architectures, methods, and AWS tools for selecting, evaluating, customizing, monitoring, governing, and deploying large language models in production.
A hands-on demonstration of Amazon Q Developer in VS Code and the Amazon Q CLI, from code suggestions to shell commands and Lambda deployment.
An intermediate overview of Amazon Bedrock’s core components, from knowledge bases and agents to prompt engineering and safeguards for generative AI applications.
Explore generative AI’s risks and impact, then use Amazon Q Business and Amazon Q Developer for data analysis, coding, and troubleshooting.
Explore Amazon Q Business through hands-on demonstrations of connectors, content analysis, applications, guardrails, and API invocation for workplace productivity.
Khám phá vòng đời ứng dụng AI tạo sinh, từ xác định trường hợp sử dụng và chọn mô hình nền tảng đến tùy chỉnh, đánh giá và triển khai.
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