Generative AI for Business Leaders
Earned 4月 5, 2024 EDT
App Dev with Gemini
Earned 3月 11, 2024 EDT
Getting Started with the Vertex AI Gemini API
Earned 3月 8, 2024 EST
Multimodality with Gemini
Earned 3月 8, 2024 EST
Custom Search with Embeddings in Vertex AI
Earned 3月 8, 2024 EST
ベクトル検索とエンベディング
Earned 3月 7, 2024 EST
Virtual Agent Development in Dialogflow ES for Software Devs
Earned 3月 6, 2024 EST
CCAI Operations and Implementation
Earned 3月 6, 2024 EST
Virtual Agent Development in Dialogflow CX for Software Devs
Earned 3月 5, 2024 EST
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned 3月 5, 2024 EST
Virtual Agent Development in Dialogflow ES for Citizen Devs
Earned 3月 5, 2024 EST
Contact Center AI: Conversational Design Fundamentals
Earned 3月 1, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned 3月 1, 2024 EST
Text Prompt Engineering Techniques
Earned 2月 26, 2024 EST
Search with AI Applications
Earned 2月 23, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned 2月 23, 2024 EST
Generative AI Explorer : Vertex AI
Earned 2月 22, 2024 EST
Vertex AI Studio の概要
Earned 2月 21, 2024 EST
Generative AI Fundamentals
Earned 2月 21, 2024 EST
責任ある AI: Google Cloud における AI に関する原則の適用
Earned 2月 20, 2024 EST
責任ある AI の概要
Earned 2月 20, 2024 EST
大規模言語モデルの概要
Earned 2月 20, 2024 EST
生成 AI の概要
Earned 2月 20, 2024 EST
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned 2月 20, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned 2月 20, 2024 EST
Smart Analytics, Machine Learning, and AI on Google Cloud - 日本語版
Earned 1月 17, 2024 EST
Google Cloud でのバッチデータ パイプラインの構築
Earned 1月 8, 2024 EST
Google Cloud でデータレイクとデータ ウェアハウスを構築する
Earned 12月 12, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals - 日本語版
Earned 12月 11, 2023 EST
This structured course is for developers interested in building intelligent agents using the Agent Development Kit (ADK). It combines hands-on experience, core concepts, and practical application, to provide a comprehensive guide to using ADK. You can also join our community of Google Cloud experts and peers to ask questions, collaborate on answers, and connect with the Googlers making the products you use every day.
詳細
Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.
詳細
このコースでは、BigQuery の生成 AI タスクで AI / ML モデルを使用する方法をご紹介します。顧客管理を含む実際のユースケースを通して、Gemini モデルを使用してビジネス上の問題を解決するワークフローを学びます。また、理解を深めるために、このコースでは SQL クエリと Python ノートブックの両方を使用したコーディング ソリューションの詳細な手順も提供しています。
詳細
このコースでは、Google Agent Development Kit を使用して複雑なマルチエージェント システムを構築する方法を学びます。各種ツールを備えた複数のエージェントを構築し、それらのエージェントを親子関係とフローで接続してエージェント間の対話方法を定義します。構築したエージェントは、ローカルで実行するとともに、Vertex AI Agent Engine にデプロイしてマネージド エージェント フローとして実行します。このとき、インフラストラクチャに関する決定やリソースのスケーリングは、Agent Engine によって行われます。
これらのラボは、このプロダクトのプレリリース版に基づいています。メンテナンスの更新が提供された場合、これらのラボに遅延が生じる可能性があります。
詳細
An LLM-based application can process language in a way that resembles thought. But if you want to extend its capabilities to take actions by running other functions you have coded, you will need to use function calling. This can also be referred to as tool use. Additionally, you can give a model the ability to search Google or search a data store of documents to ground its responses. In other words, to base its answers on that information. In this course, you’ll explore these concepts.
詳細
このコースでは、Google のポータブル UI ツールキットである Flutter を使用してアプリを開発し、そのアプリを Google の生成 AI モデル ファミリーである Gemini と統合する方法について学びます。また、AI エージェントとアプリケーションを構築、管理するための Google のプラットフォームである Vertex AI Agent Builder も使用します。
詳細
This course provides an introduction to Looker Studio’s powerful features for data visualization and reporting. Learn to transform raw data into insightful reports by mastering various visualization options, connecting to diverse data sources, and implementing interactive controls such as filters. Explore data blending techniques to combine information from multiple sources and unlock deeper insights. Through hands-on exercises you'll gain the skills to create compelling, dynamic reports that effectively communicate data-driven stories.
詳細
In this introductory course, you'll learn how Looker can help you explore, analyze, and visualize your data to drive better decisions. Through a combination of video lectures and demos, you'll discover how to connect to various data sources, build interactive dashboards, and perform effective data analysis. Whether you're a data analyst, BI analyst, data scientist or business user, this course will equip you with the foundational knowledge to start using Looker effectively, regardless of your background.
詳細
このコースでは、BigQuery で検索拡張生成（RAG）ソリューションを使用して AI ハルシネーションを軽減する方法を説明します。エンベディングの作成、ベクトル空間の検索、改善された回答の生成を含む RAG ワークフローについて解説し、これらの手順の背後にある概念的な理由と、BigQuery を使用した実践的な実装方法についても説明します。このコースを完了すると、BigQuery、Gemini などの生成 AI モデル、エンベディング モデルを使用して RAG パイプラインを構築し、独自の AI ハルシネーションのユースケースに対処できるようになります。
詳細
Google が持つ検索と AI の専門知識を Gemini Enterprise と融合させましょう。Gemini Enterprise は、従業員が単一の検索バーでドキュメント ストレージ、メール、チャット、チケット発行システム、その他のデータソースから特定の情報を検索できるよう設計された強力なツールです。また、Gemini Enterprise アシスタントは、ブレインストーミング、調査、ドキュメントの概要作成、カレンダーの予定への同僚の招待といったアクションの実行を支援し、あらゆる種類の知識労働や共同作業を加速させます。（Gemini Enterprise は以前 Google Agentspace という名前でした。このコースでは以前のプロダクト名が使用されている場合があります。）
詳細
This course equips full-stack mobile and web developers with the skills to integrate generative AI features into their applications using LangChain. You'll learn how to leverage LangChain’s capabilities for backend flows and seamless model execution, all within the familiar environment of Python. The course guides you through the entire process, from prototyping to production, ensuring a smooth journey in building next-generation AI-powered applications.
詳細
「BigQuery ML を使用した予測モデリング向けのデータ エンジニアリング」のスキルバッジを獲得できる中級コースを修了すると、 Dataprep by Trifacta を使用した BigQuery へのデータ変換パイプラインの構築、 Cloud Storage、Dataflow、BigQuery を使用した抽出、変換、読み込み（ETL）ワークフローの構築、 BigQuery ML を使用した ML モデルの構築に関するスキルを実証できます。
詳細
「BigQuery ML を使用した ML モデルの作成」コースの中級スキルバッジを獲得できるアクティビティを修了すると、 BigQuery ML を使用して ML モデルを作成および評価し、データを予測するスキルを証明できます。
詳細
This course explores the best practices, methods and tools to programmatically lead CCAI virtual agent delivery. It includes a high level overview of the end to end journey for building and deploying a virtual agent, as well as the core tenets to create a strong delivery culture. Additionally, this course covers the best practices for workflow management, defect tracking, release management and post-release support to ensure optimal virtual agent performance.
詳細
In this course, you'll learn to develop AI agents that answer questions using websites, documents, or structured data. You will explore AI Applications and understand the advantages of data store agents, including their scalability and security.
You'll learn about different data store types and also discover how to connect data stores to agents and add personalization for enhanced responses.
Finally, you'll gain insights into common search configurations and troubleshooting techniques.
詳細
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.
詳細
This course explores the different products and capabilities of Gemini Enterprise for Customer Experience and Conversational Agents. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.
詳細
(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
詳細
In this course, you will learn about advanced methods and tools to monitor the performance of your Conversational agent in Conversational Agents. Please note Dialogflow CX was recently renamed to Conversational Agents and this course is in the process of being updated to reflect the new product name for Dialogflow CX.
詳細
This course explores advanced technical considerations to optimize Webhook connectivity for comprehensive, end-to-end, Conversational Agent self-service experiences. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
詳細
Explore Playbooks and their implementation of the ReAct pattern for building conversational agents. You will learn how to construct a Playbook, set up goals and instructions to build a chatbot in natural language, and learn to test and deploy your solution.
詳細
This course will equip you with the tools to develop complex conversational experiences in Conversational Agents capable of identifying the user intent and routing it to the right self service flow. Please note Dialogflow CX was recently renamed to Conversational Agents, Virtual agent renamed to Conversational agent, and CCAI Insights were renamed to Conversational Insights, and this course is in the process of being updated to reflect the new product names for Dialogflow CX, and Virtual Agent, CCAI Insights.
詳細
Learn about building conversational AI voice and chat integrations, including how telephony systems can connect with Google to enable phone-based interactions within the Conversational AI ecosystem. Explore key topics such as the differences between chat and voice conversations, the writing process for creating conversation scripts, and the beginning of the interrogative series and closing sequence.
詳細
This on-demand course provides partners the skills required to design, deploy, and monitor Vertail AI Search for Commerce solutions including retail search and recommendation AI for enterprise customers.
詳細
このコースでは、TensorFlow と Keras を使用した ML モデルの構築、ML モデルの精度の向上、スケーリングに対応した ML モデルの作成について取り上げます。
詳細
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.
In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
詳細
An AI-driven Contact Center as a Service (CCaaS) solution that is built natively on Google Cloud. The Implementation course provides Partners with essential training about the delivery of key features and functionality. The course explores how to leverage your key understanding of the product into successful customer implementation engagements with tips, best practices, guides, and more.
Note: This product was previously called Contact Center AI (CCAI) Platform you may see references to that name still in the course, however the course is technically correct.
詳細
This course will equip you with the tools to develop complex conversational experiences in Dialogflow CX capable of identifying the user intent and routing it to the right self service flow.
Learn how Gemini can revolutionize your ability to develop applications! This course helps developers go beyond the basics and learn how to integrate Gemini into their workflows.
「Dataplex を使用したデータメッシュの構築」入門コースを修了してスキルバッジを獲得すると、Dataplex を使用してデータメッシュを構築し、 Google Cloud 上のデータ セキュリティ、ガバナンス、検出を強化するスキルを実証できます。このコースでは、Dataplex でアセットにタグを付け、IAM ロールを割り当て、データ品質を評価する方法を練習し、そのスキルをテストします。
詳細
このコースでは拡散モデルについて説明します。拡散モデルは ML モデル ファミリーの一つで、最近、画像生成分野での有望性が示されました。拡散モデルは物理学、特に熱力学からインスピレーションを得ています。ここ数年、拡散モデルは研究と産業界の両方で広まりました。拡散モデルは、Google Cloud の最先端の画像生成モデルやツールの多くを支える技術です。このコースでは、拡散モデルの背景にある理論と、モデルを Vertex AI でトレーニングしてデプロイする方法について説明します。
詳細
A Business Leader in Generative AI can articulate the capabilities of core cloud Generative AI products and services and understand how they benefit organizations. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey and how they can leverage Google Cloud's generative AI products to overcome these challenges.
詳細
Unlock the power of Google Cloud's cutting-edge Vertex AI Gemini API to craft innovative multimodal applications. This hands-on course delves into the integration of the Vertex AI SDK for Python, guiding you through the generation of sophisticated responses powered by the Gemini Pro and Gemini Pro Vision models. Get ready to build, deploy, and harness the transformative capabilities of multimodal AI within your own projects.
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
詳細
Get hands-on with the Gemini Pro and Gemini Pro Vision models through our new labs. This course gives you a unique chance to explore these powerful AI tools while our training content is still in development. Learn to interact with the models using the Vertex AI Gemini API and cURL commands, and help us create the best possible learning experience around this technology.
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
詳細
Delve into the power of multimodal AI with this project-based course using Gemini. Master essential techniques and build advanced applications. You will:
- Experiment with multimodal use cases to expand application possibilities
- Implement recommendation systems that combine suggestions with clear reasoning
- Design a powerful document search engine using multimodal RAG methods
Important Disclaimer: Please note that these labs are under active development. Functionality may occasionally change or break unexpectedly, and content might be removed or altered without notice. By proceeding with this course, you acknowledge this potential disruption.
詳細
This course explores Google Cloud technologies to create and generate embeddings. Embeddings are numerical representations of text, images, video and audio, and play a pivotal role in many tasks that involve the identification of similar items, like Google searches, online shopping recommendations, and personalized music suggestions. Specifically, you’ll use embeddings for tasks like classification, outlier detection, clustering and semantic search.
You’ll combine semantic search with the text generation capabilities of an LLM to build Retrieval Augmented Generation (RAG) systems and question-answering solutions, on your own proprietary data using Google Cloud’s Vertex AI.
詳細
このコースでは、AI を活用した検索テクノロジー、ツール、アプリケーションについて学びます。ベクトル エンベディングを利用するセマンティック検索、セマンティック アプローチとキーワード アプローチを組み合わせたハイブリッド検索、グラウンディング対応 AI エージェントとして AI のハルシネーションを最小限に抑える検索拡張生成（RAG）をご紹介します。Vertex AI Vector Search を実践的な経験を積んで、インテリジェントな検索エンジンを構築しましょう。
詳細
Welcome to "CCAI Virtual Agent Development in Dialogflow ES for Software Developers", the third course in the "Customer Experiences with Contact Center AI" series.
In this course, learn to use additional features of Dialogflow ES for your virtual agent, create a Firestore instance to store customer data, and implement cloud functions that access the data. With the ability to read and write customer data, learner’s virtual agents are conversationally dynamic and able to defer contact center volume from human agents. You'll be introduced to methods for testing your virtual agent and logs which can be useful for understanding issues that arise. Lastly, learn about connectivity protocols, APIs, and platforms for integrating your virtual agent with services already established for your business.
詳細
Welcome to "CCAI Operations and Implementation", the fourth course in the "Customer Experiences with Contact Center AI" series. In this course, learn some best practices for integrating conversational solutions with your existing contact center software, establishing a framework for human agent assistance, and implementing solutions securely and at scale. In this course, you'll be introduced to Agent Assist and the technology it uses so you can delight your customers with the efficiencies and accuracy of services provided when customers require human agents, connectivity protocols, APIs, and platforms which you can use to create an integration between your virtual agent and the services already established for your business, Dialogflow's Environment Management tool for deployment of different versions of your virtual agent for various purposes, compliance measures and regulations you should be aware of when bringing your virtual agent to production, and you'll be given tips from virtua…
詳細
Welcome to "Virtual Agent Development in Dialogflow CX for Software Devs", the third course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to develop more customized customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to more advanced and customized handling for virtual agent conversations that need to look up and convey dynamic data, and methods available to you for testing your virtual agent and logs which can be useful for understanding issues that arise.
This is an intermediate course, intended for learners with the following type of role:
Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API.
詳細
Welcome to "Virtual Agent Development in Dialogflow CX for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). In this course, you'll be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations using Dialogflow CX.
詳細
Welcome to "Virtual Agent Development in Dialogflow ES for Citizen Devs", the second course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to develop customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will use Dialogflow ES to create virtual agents and test them using the Dialogflow ES simulator. This course also provides best practices on developing virtual agents. You will also be introduced to adding voice (telephony) as a communication channel to your virtual agent conversations. Through a combination of presentations, demos, and hands-on labs, participants learn how to create virtual agents.
This is an intermediate course, intended for learners with the following types of roles:
Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows.
Citizen developers: Creates new business applications fo…
詳細
Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series.
In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.
詳細
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.
詳細
Text Prompt Engineering Techniques introduces you to consider different strategic approaches & techniques to deploy when writing prompts for text-based generative AI tasks.
詳細
(Previously named "Developing apps with Vertex AI Agent Builder: Search". Please note there maybe instances in this course where previous product names and titles are used)
Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use AI Applications to integrate enterprise-grade generative AI search.
詳細
(This course was previously named Multimodal Prompt Engineering with Gemini and PaLM) This course teaches how to use Vertex AI Studio, a Google Cloud console tool for rapidly prototyping and testing generative AI models. You learn to test sample prompts, design your own prompts, and customize foundation models to handle tasks that meet your application's needs. Whether you are looking for text, chat, code, image or speech generative experiences Vertex AI Studio offers you an interface to work with and APIs to integrate your production application.
詳細
This content is deprecated. Please see the latest version of the course, here.
詳細
このコースでは、生成 AI モデルとのやりとり、ビジネス アイデアのプロトタイプ作成、本番環境へのリリースを行うツールである Vertex AI Studio をご紹介します。現実感のあるユースケースや、興味深い講義、ハンズオンラボを通して、プロンプトの作成から成果の実現に至るまでのライフサイクルを詳細に学び、Gemini マルチモーダル アプリケーションの開発、プロンプトの設計、モデルのチューニングに Vertex AI を活用する方法を学習します。Vertex AI Studio を利用することで、生成 AI をプロジェクトに最大限に活かせるようになることを目指します。
詳細
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.
詳細
企業における AI と ML の利用が拡大し続けるなか、責任を持ってそれを構築することの重要性も増しています。多くの企業にとっての課題は、責任ある AI と口で言うのは簡単でも、それを実践するのは難しいということです。このコースは、責任ある AI を組織で運用化する方法を学びたい方に最適です。
このコースでは、Google Cloud が責任ある AI を現在どのように運用化しているかを、ベスト プラクティスや教訓と併せて学び、責任ある AI に対する独自のアプローチを構築するためのフレームワークとして活用できるようにします。
詳細
この入門レベルのマイクロラーニング コースでは、責任ある AI の概要と重要性、および Google が責任ある AI を自社プロダクトにどのように実装しているのかについて説明します。また、Google の AI に関する 7 つの原則についても説明します。
詳細
このコースは、大規模言語モデル（LLM）とは何か、どのようなユースケースで活用できるのか、プロンプトのチューニングで LLM のパフォーマンスを高めるにはどうすればよいかについて学習する、入門レベルのマイクロ ラーニング コースです。独自の生成 AI アプリを開発する際に利用できる Google ツールも紹介します。
詳細
この入門レベルのマイクロラーニング コースでは、生成 AI の概要、利用方法、従来の機械学習の手法との違いについて説明します。独自の生成 AI アプリを作成する際に利用できる Google ツールも紹介します。
詳細
This course explores the different products and capabilities of Gemini Enterprise for Customer Experience and Conversational Agents. Additionally, it covers the foundational principles of conversation design to craft engaging and effective experiences that emulate human-like experiences specific to the Chat channel.
詳細
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.
詳細
ML をデータ パイプラインに組み込むと、データから分析情報を抽出する能力を向上できます。このコースでは、Google Cloud でデータ パイプラインに ML を含める複数の方法について説明します。カスタマイズがほとんど、またはまったく必要ない場合のために、このコースでは AutoML について説明します。よりカスタマイズされた ML 機能については、Notebooks と BigQuery の機械学習（BigQuery ML）を紹介します。また、Vertex AI を使用して ML ソリューションを本番環境に導入する方法も説明します。
データレイクとデータ ウェアハウスを使用する従来のアプローチは効果的ですが、特に大規模な企業環境においては欠点があります。このコースでは、データ レイクハウスのコンセプトと、データ レイクハウスの作成に使用する Google Cloud プロダクトについて説明します。レイクハウス アーキテクチャは、オープン スタンダードのデータソースを使用し、データレイクとデータ ウェアハウスの優れた機能を組み合わせて、両者の欠点の多くに対処します。
詳細
このコースでは、データから AI へのライフサイクルをサポートする Google Cloud のビッグデータと ML のプロダクトやサービスを紹介します。また、Google Cloud で Vertex AI を使用してビッグデータ パイプラインと ML モデルを作成する際のプロセス、課題、メリットについて説明します。
Build intelligent agents with Agent Development Kit (ADK)
Earned 10月 21, 2025 EDT
Data Lake Modernization on Google Cloud: Cloud Composer
Earned 8月 14, 2025 EDT
BigQuery で Gemini モデルを操作する
Earned 8月 13, 2025 EDT
Agent Development Kit（ADK）と Agent Engine を使用してマルチエージェント システムをデプロイする
Earned 8月 12, 2025 EDT
Empower Gen AI apps with tool use
Earned 8月 12, 2025 EDT
Vertex AI と Flutter による 生成 AI エージェントの構築
Earned 8月 12, 2025 EDT
Looker Studio Essentials
Earned 7月 28, 2025 EDT
Introduction to Looker
Earned 7月 25, 2025 EDT
エンベディング作成、ベクトル検索、BigQuery での RAG
Earned 6月 6, 2025 EDT
Gemini Enterprise で知識の共有を加速させる
Earned 6月 6, 2025 EDT
Orchestrating Gen AI Applications with LangChain
Earned 6月 5, 2025 EDT
BigQuery ML を使用した予測モデリング向けのデータ エンジニアリング
Earned 2月 4, 2025 EST
BigQuery ML を使用した ML モデルの作成
Earned 1月 16, 2025 EST
DFCX Virtual Agent Delivery Framework
Earned 7月 4, 2024 EDT
Extend CX Agents with Vertex AI Search data stores
Earned 7月 4, 2024 EDT
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned 5月 30, 2024 EDT
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned 5月 30, 2024 EDT
Search with AI Applications
Earned 5月 30, 2024 EDT
Advanced Performance Measurement
Earned 5月 29, 2024 EDT
Advanced Webhook Concepts
Earned 5月 28, 2024 EDT
Generative Playbooks
Earned 5月 28, 2024 EDT
Building Complex Self-Service Experiences in Conversational Agents
Earned 5月 27, 2024 EDT
Conversational AI Voice and Chat Integrations
Earned 5月 27, 2024 EDT
Vertex AI Search for Commerce
Earned 5月 27, 2024 EDT
Google Cloud での Keras を使った ML モデルの構築、トレーニング、デプロイ
Earned 5月 22, 2024 EDT
Develop Advanced Enterprise Search and Conversation Applications
Earned 5月 21, 2024 EDT
BigQuery のデータから分析情報を引き出す
Earned 5月 21, 2024 EDT
BigQuery でデータ ウェアハウスを構築する
Earned 5月 17, 2024 EDT
Understanding LookML in Looker
Earned 5月 16, 2024 EDT
Contact Center as a Service Implementation
Earned 5月 8, 2024 EDT
Building Complex End to End Self-Service Experiences in Dialogflow CX
Earned 5月 6, 2024 EDT
Developing Data Models with LookML - 日本語版
Earned 4月 24, 2024 EDT
Analyzing and Visualizing Data in Looker - 日本語版
Earned 4月 24, 2024 EDT
Dataflow を使用したサーバーレスのデータ処理: 基礎
Earned 4月 17, 2024 EDT
Improving developer velocity with Gemini Code Assist
Earned 4月 17, 2024 EDT
BigQuery でデータ ウェアハウスを構築する
Earned 4月 11, 2024 EDT
Dataplex を使用したデータメッシュの構築
Earned 4月 10, 2024 EDT
画像生成の概要
Earned 4月 5, 2024 EDT
Generative AI for Business Leaders
Earned 4月 5, 2024 EDT
App Dev with Gemini
Earned 3月 11, 2024 EDT
Getting Started with the Vertex AI Gemini API
Earned 3月 8, 2024 EST
Multimodality with Gemini
Earned 3月 8, 2024 EST
Custom Search with Embeddings in Vertex AI
Earned 3月 8, 2024 EST
ベクトル検索とエンベディング
Earned 3月 7, 2024 EST
Virtual Agent Development in Dialogflow ES for Software Devs
Earned 3月 6, 2024 EST
CCAI Operations and Implementation
Earned 3月 6, 2024 EST
Virtual Agent Development in Dialogflow CX for Software Devs
Earned 3月 5, 2024 EST
Virtual Agent Development in Dialogflow CX for Citizen Devs
Earned 3月 5, 2024 EST
Virtual Agent Development in Dialogflow ES for Citizen Devs
Earned 3月 5, 2024 EST
Contact Center AI: Conversational Design Fundamentals
Earned 3月 1, 2024 EST
Develop Advanced Enterprise Search and Conversation Applications
Earned 3月 1, 2024 EST
Text Prompt Engineering Techniques
Earned 2月 26, 2024 EST
Search with AI Applications
Earned 2月 23, 2024 EST
Building Gen AI Apps with Vertex AI: Prompting and Tuning
Earned 2月 23, 2024 EST
Generative AI Explorer : Vertex AI
Earned 2月 22, 2024 EST
Vertex AI Studio の概要
Earned 2月 21, 2024 EST
Generative AI Fundamentals
Earned 2月 21, 2024 EST
責任ある AI: Google Cloud における AI に関する原則の適用
Earned 2月 20, 2024 EST
責任ある AI の概要
Earned 2月 20, 2024 EST
大規模言語モデルの概要
Earned 2月 20, 2024 EST
生成 AI の概要
Earned 2月 20, 2024 EST
Introduction to Gemini Enterprise for Customer Experience and Conversational Agents
Earned 2月 20, 2024 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps
Earned 2月 20, 2024 EST
Smart Analytics, Machine Learning, and AI on Google Cloud - 日本語版
Earned 1月 17, 2024 EST
Google Cloud でのバッチデータ パイプラインの構築
Earned 1月 8, 2024 EST
Google Cloud でデータレイクとデータ ウェアハウスを構築する
Earned 12月 12, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals - 日本語版
Earned 12月 11, 2023 EST