Transformer Models and BERT Model - 繁體中文
Earned Aug 17, 2023 EDT
Attention Mechanism - 繁體中文
Earned Aug 16, 2023 EDT
Encoder-Decoder Architecture - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Image Generation - 繁體中文
Earned Aug 16, 2023 EDT
Generative AI Fundamentals - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Responsible AI - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Large Language Models - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Generative AI - 繁體中文
Earned Aug 14, 2023 EDT
Demonstrate your ability to implement updated prompt engineering techniques and utilize several of Gemini's key capacilities including multimodal understanding and function calling. Then integrate generative AI into a RAG application deployed to Cloud Run. This course contains labs that are to be used as a test environment. They are deployed to test your understanding as a learner with a limited scope. These technologies can be used with fewer limitations in a real world environment.
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Learn to use LangChain to call Google Cloud LLMs and Generative AI Services and Datastores to simplify complex applications' code.
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In this course, you'll use text embeddings for tasks like classification, outlier detection, text clustering and semantic search. You'll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) solutions, such as for question-answering systems, using Google Cloud's Vertex AI and Google Cloud databases.
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This course on Integrate Vertex AI Search and Conversation into Voice and Chat Apps is composed of a set of labs to give you a hands on experience to interacting with new Generative AI technologies. You will learn how to create end-to-end search and conversational experiences by following examples. These technologies complement predefined intent-based chat experiences created in Dialogflow with LLM-based, generative answers that can be based on your own data. Also, they allow you to porvide enterprise-grade search experiences for internal and external websites to search documents, structure data and public websites.
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Text Prompt Engineering Techniques introduces you to using a generative model and prompting techniques as a creative process that to generate ideations, for example memes and marketing campaigns. It also shows how to use the PaLM and Gemini APIs and large language models to analyze and manipulate text and answer questions.
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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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隨著企業持續擴大使用人工智慧和機器學習，以負責任的方式發展相關技術也日益重要。對許多企業來說，談論負責任的 AI 技術可能不難，如何付諸實行才是真正的挑戰。如要瞭解如何在機構中導入負責任的 AI 技術，本課程絕對能助您一臂之力。
您可以從中瞭解 Google Cloud 目前採取的策略、最佳做法和經驗談，協助貴機構奠定良好基礎，實踐負責任的 AI 技術。
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本課程將介紹 Vertex AI 上的 Generative AI Studio，說明如何用此產品設計生成式 AI 模型的原型及自訂生成式 AI 模型，以利您在應用程式中使用模型的功能。課程中，您可以透過 Generative AI Studio 示範教學逐步認識 Generative AI Studio，並瞭解產品功能、選項與使用方式。課程最後，您可以在實作研究室應用所學，並進行測驗來評估學習成果。
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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。
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完成 Prompt Design in Vertex AI 技能徽章入門課程，即可證明您具備下列技能： 在 Vertex AI 設計提示、分析圖片，以及運用多模態模型生成內容。瞭解如何建立有效的提示、引導生成式 AI 輸出內容， 以及將 Gemini 模型用於實際的行銷情境。 「技能徽章」是 Google Cloud 核發的獨家數位徽章， 用於肯定您在 Google Cloud 產品與服務方面的精通程度， 代表您已通過測驗，能在互動式實作環境中應用相關知識。完成 本課程及結業評量挑戰研究室，即可取得技能徽章 並與親友分享。
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Vertex AI Studio 可用於生成式 AI 模型的原型設計和自訂。本課程會介紹這項工具，並透過沉浸式課程、生動示範和實作研究室，讓您將瞭解生成式 AI 的工作流程，以及如何將 Vertex AI Studio 運用在多模態版 Gemini 應用程式、提示設計和模型調整。目的是讓您能運用 Vertex AI Studio，發揮專案中這些模型的潛能。
本課程將介紹擴散模型，這是一種機器學習模型，近期在圖像生成領域展現亮眼潛力。概念源自物理學，尤其深受熱力學影響。過去幾年來，在學術界和業界都是炙手可熱的焦點。在 Google Cloud 中，擴散模型是許多先進圖像生成模型和工具的基礎。課程將介紹擴散模型背後的理論，並說明如何在 Vertex AI 上訓練和部署這些模型。
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完成「Introduction to Generative AI」、「Introduction to Large Language Models」和「Introduction to Responsible AI」課程，即可獲得技能徽章。通過最終測驗，就能展現您對生成式 AI 基本概念的掌握程度。
「技能徽章」是 Google Cloud 核發的數位徽章，用於表彰您對 Google Cloud 產品和服務的相關知識。您可以將技能徽章公布在社群媒體的個人資料中，向其他人分享您的成果。
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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。
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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。
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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。
Build and Deploy a Generative AI solution using a RAG framework
Earned Aug 21, 2024 EDT
Orchestrate LLM solutions with LangChain
Earned Aug 19, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned Aug 19, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned Aug 15, 2024 EDT
Text Prompt Engineering Techniques
Earned Jul 22, 2024 EDT
Generative AI Fundamentals
Earned Jul 21, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud - 繁體中文
Earned Jul 21, 2024 EDT
Introduction to Generative AI Studio - 繁體中文
Earned Jul 21, 2024 EDT
Introduction to Generative AI - 繁體中文
Earned Jul 21, 2024 EDT
Prompt Design in Vertex AI
Earned Jul 21, 2024 EDT
Introduction to Vertex AI Studio - 繁體中文
Earned Aug 17, 2023 EDT
Create Image Captioning Models - 繁體中文
Earned Aug 17, 2023 EDT
Transformer Models and BERT Model - 繁體中文
Earned Aug 17, 2023 EDT
Attention Mechanism - 繁體中文
Earned Aug 16, 2023 EDT
Encoder-Decoder Architecture - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Image Generation - 繁體中文
Earned Aug 16, 2023 EDT
Generative AI Fundamentals - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Responsible AI - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Large Language Models - 繁體中文
Earned Aug 16, 2023 EDT
Introduction to Generative AI - 繁體中文
Earned Aug 14, 2023 EDT