成为会员时间：2025
Enterprise Readiness in Generative AI
Earned Oct 14, 2025 EDT
負責任的 AI 技術簡介
Earned Oct 14, 2025 EDT
大型語言模型簡介
Earned Oct 14, 2025 EDT
Google Cloud: Prompt Engineering Guide
Earned Oct 13, 2025 EDT
生成式 AI 簡介
Earned Oct 13, 2025 EDT
Explore the four pillars of Enterprise Readiness in generative AI: data governance and privacy, security and compliance support, infrastructure reliability and sustainability, and responsible AI. You will also learn how these pillars address concerns about data privacy and security. Learn about customizing foundation models with your data while keeping your data safe using adapter layers, how to keep your AI models safe and compliant when deploying them across the world, and the multiple layers of encryption, rigorous controls, supply chain audits, and ongoing security testing that are built into Google Cloud. You will also learn about security controls such as VPC, customer-managed encryption keys, access transparency, and data residency zones. And explore enterprise controls, certifications, and responsible AI tooling available in Vertex AI to ensure your data remains secure and compliant with global regulations when deploying generative AI models.
這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。
這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。
Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.
這個入門微學習課程主要說明生成式 AI 的定義和使用方式，以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具，協助您開發自己的生成式 AI 應用程式。