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BHARGAV RITWICK

メンバー加入日: 2025

ダイヤモンド リーグ

11073 ポイント
Build Agents with the Agent Development Kit Earned 8月 11, 2026 EDT
Build with the Managed Agents API on Gemini Enterprise Agent Platform Earned 8月 11, 2026 EDT
Evaluate and Improve Agent Development Kit Agents Earned 8月 11, 2026 EDT
Accelerate Agent Development with Antigravity and Agents CLI Earned 8月 10, 2026 EDT
Accelerate Development with Antigravity Earned 8月 10, 2026 EDT
Gemini でマルチモーダル データを分析し、推論する Earned 6月 20, 2026 EDT
Engineer Effective Prompts for Generative Models Earned 5月 28, 2026 EDT
Create media search and media recommendations applications with AI Applications Earned 5月 27, 2026 EDT
Recommendations with AI Applications Earned 5月 27, 2026 EDT
Gemini Enterprise で知識の共有を加速させる Earned 5月 27, 2026 EDT
Add Agents to Gemini Enterprise Earned 5月 27, 2026 EDT
Use a Third-Party Identity Provider with Workforce Identity Federation Earned 5月 27, 2026 EDT
[DEPRECATED] Introduction to NotebookLM Earned 5月 27, 2026 EDT
Create Data Stores for Gen AI Applications Earned 5月 27, 2026 EDT
Introduction to AI Applications Earned 5月 27, 2026 EDT
エージェントの基礎 Earned 1月 10, 2026 EST
Configure AI Applications to optimize search results Earned 1月 10, 2026 EST
Improve Agent Search Results on Agent Platform Earned 1月 10, 2026 EST
Agent Search Analytics on Agent Platform Earned 1月 10, 2026 EST
Agent Search UI configurations on Agent Platform Earned 1月 10, 2026 EST
Create and maintain Vertex AI Search data stores Earned 1月 3, 2026 EST
Build search and recommendations applications with AI Applications Earned 1月 3, 2026 EST
Deploy an Agent with Agent Development Kit (ADK) Earned 12月 31, 2025 EST
Deploy a RAG application with vector search in Firestore Earned 12月 28, 2025 EST
Integrate Vertex AI Search and Conversation into Voice and Chat Apps Earned 12月 27, 2025 EST
Deploy and Evaluate Model Garden Models Earned 12月 26, 2025 EST
Extend Gemini with controlled generation and Tool use Earned 12月 25, 2025 EST
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 12月 25, 2025 EST
BigQuery ML を使用した ML モデルの作成 Earned 12月 25, 2025 EST
Google Cloud の ML API 用にデータを準備 Earned 12月 25, 2025 EST
開発者向けの責任ある AI: プライバシーと安全性 Earned 12月 25, 2025 EST
開発者向けの責任ある AI: 解釈可能性と透明性 Earned 12月 25, 2025 EST
発者向けの責任ある AI: 公平性とバイアス Earned 12月 25, 2025 EST
Google Cloud での生成 AI アプリの作成 Earned 12月 25, 2025 EST
Vertex AI を使用した ML オペレーション(MLOps): モデルの評価 Earned 12月 25, 2025 EST
大規模言語モデルの概要 Earned 12月 25, 2025 EST
生成 AI の概要 Earned 12月 25, 2025 EST
生成 AI のための ML オペレーション(MLOps) Earned 12月 25, 2025 EST

In this course, you'll learn to use the Agent Development Kit (ADK) to build systems where multiple AI agents collaborate on complex tasks. You'll start with the ADK agent model: how ADK represents agents, tools, and runners, and how a single agent is configured and run. You'll then make tools the model can call, persist session state across agents, and instrument the execution lifecycle with callbacks and plugins. Next, you'll orchestrate multiple agents using ADK's template workflow agents and graph-based workflows, and ground them in enterprise data through multi-source retrieval and MCP integrations. Finally, you'll deploy a multi-agent system to Agent Runtime as a managed service and register and share it through Gemini Enterprise so users across an organization can reach it.

詳細

In this course, you'll learn to build and run enterprise agents on the Managed Agents API, the managed agent runtime on Gemini Enterprise Agent Platform. Three conceptual lessons give you the mental model. You'll learn why a real business task needs an agent rather than a chat model. You'll examine how the platform splits into a control plane that defines agents and a data plane that runs them. You'll learn how to assemble an agent from a definition, a sandboxed environment, mounted data, tools, and skills. And you'll learn how to run it with background interactions, a streamed reason-act loop, resilient typed results, and state that persists across turns. You then put that model to work in a hands-on lab, where you build, run, and harden a retail merchandising agent for Cymbal Retail from an empty project to a production-shaped deployment. By the end, you'll be able to design, build, and operate a managed agent of your own.

詳細

Complete the Evaluate and Improve Agent Development Kit Agents skill badge to demonstrate your ability to use ADK's evaluation tools to "hill climb" — making measurable, iterative improvements to an agent. You will run an initial evaluation to establish a baseline, apply optimization techniques, and re-evaluate the agent to measure your success.

詳細

In this course, you’ll learn to simplify the creation of autonomous enterprise agents using the Agent Development Kit (ADK) and you will learn how to leverage the power of Antigravity and the Agents CLI to transform your agent development workflow. In this course. You will explore practical techniques to automate repetitive tasks and significantly accelerate the creation of robust, enterprise-grade agents, ensuring scalability and efficiency in your AI projects.

詳細

Complete the Accelerate Development with Antigravity skill badge to demonstrate your proficiency in using the Antigravity IDE for developing agentic workflows. You will be tasked with configuring an MCP server, authoring custom agent skills and rules, prototyping with the Agents CLI, and deploying to the Google Cloud Agent Runtime. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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「Gemini でマルチモーダル データを分析し、推論する」の中級スキルバッジを獲得すると、Gemini 2.0 Flash を使用してテキスト、画像、音声(楽譜として表現)、動画データを分析し、これらの情報の組み合わせで推論を行い、結論を導き出して、分析情報を抽出するスキルを実証できます。

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Learn a variety of strategies and techniques to engineer effective prompts for generative models

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Complete the Create media search and media recommendations applications with AI Applications skill badge to demonstrate your ability to create, configure, and access media search and recommendations applications using AI Applications. Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

詳細

Do you want to keep your users engaged by suggesting content they'll love? This course equips you with the skills to build a cutting-edge recommendations app using your own data with no prior machine learning knowledge. You learn to leverage AI Applications to build recommendation applications so that audiences can discover more personalized content, like what to watch or read next, with Google-quality results customized using optimization objectives.

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

In this challenge lab, you will demonstrate your ability to add agents to a Gemini Enterprise app. You will build an agent with Agent Designer. And you will build a no-code agent with Agent Development Kit, deploy it to Agent Engine, and add it to the Gemini Enterprise app.

詳細

This course provides learners the knowledge to configure Workforce Identity Federation to grant Google Cloud and Gemini Enterprise access to users that authenticate using a third-party Identity Provider. The curriculum includes theory and demo videos covering workforce identity pools, OIDC and SAML providers, attribute mapping, IAM policies, and troubleshooting guidance.

詳細

NotebookLM is an AI-powered collaborator that helps you do your best thinking. After uploading your documents, NotebookLM becomes an instant expert in those sources so you can read, take notes, and collaborate with it to refine and organize your ideas. NotebookLM Pro gives you everything already included with NotebookLM, as well as higher utilization limits, access to premium features, and additional sharing options and analytics.

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Data stores represent a simple way to make content available to many types of generative AI applications, including search applications, recommendations engines, Gemini Enterprise apps, Agent Development Kit agents, and apps built with Google Gen AI or LangChain SDKs. Connect data from many sources include Cloud Storage, Google Drive, chat apps, mail apps, ticketing systems, third-party file storage providers, Salesforce, and many more.

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This course introduces AI Applications. You will learn about the types of apps that you can create using AI Applications, the high-level steps that its data stores automate for you, and what advanced features can be enabled for Search apps. (Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)

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このコースでは、AI エージェントの基礎について解説し、エージェントが現実の場面でどのように真価を発揮するのかを確認します。自律的で目標指向のふるまいという観点から AI システムを理解したいと考えている開発者、アーキテクト、技術的意思決定者にとっての基盤となります。

詳細

Complete the Configure AI Applications to optimize search results skill badge to demonstrate your proficiency in configuring search results from AI Applications. You will be tasked with implementing search serving controls to boost and bury results, filter entries from search results and display metadata in your search interface. Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

詳細

This course covers techniques for boosting and filtering search results, as well as the implementation of meta tags for advanced search control.

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AI Applications provides built-in analytics for your Agent Search and Gemini Enterprise apps. Learn what metrics are tracked and how to view them in this course.

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Initial deployment of Agent Search and Gemini Enterprise apps takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience. In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Gemini Enterprise apps.

詳細

Complete the Create and maintain Vertex AI Search data stores skill badge to demonstrate your proficiency in building various types of data stores used in Vertex AI Search applications. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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Complete the Build search and recommendations AI Applications skill badge to demonstrate your proficiency in deploying search and recommendation applications through AI Applications. Additionally, emphasis is placed on constructing a tailored Q&A system utilizing data stores. Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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In this challenge lab, you will demonstrate your ability to author agents using Agent Development Kit (ADK), deploy those agents to Agent Engine, and use them from a web app. Complete the challenge lab to earn a Google Cloud skill badge.

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This lab tests your ability to develop a real-world Generative AI Q&A solution using a RAG framework. You will use Firestore as a vector database and deploy a Flask app as a user interface to query a food safety knowledge base.

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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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In this skill bagde, you will demonstrate your ability to use and compare models available in the Vertex AI Model Garden. You'll deploy a model to a Vertex AI Endpoint, query other models via their API, and use Vertex AI's Gen AI evaluation service to measure the performance of multiple models.

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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!"

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「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。

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「Google Cloud の ML API 用にデータを準備」コースの入門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、 Dataprep by Trifacta を使用したデータのクリーニング、Dataflow でのデータ パイプラインの実行、Managed Service for Apache Spark でのクラスタの作成と Apache Spark ジョブの実行、 Cloud Natural Language API、Google Cloud Speech-to-Text API、Video Intelligence API などの ML API の呼び出しに関するスキルを証明できます。

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このコースでは、AI のプライバシーと安全性に関する重要なトピックを紹介します。具体的には、Google Cloud プロダクトとオープンソース ツールを使用して AI のプライバシーと安全性の推奨プラクティスを実装するための実践的な方法とツールを検証します。

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このコースでは、AI の解釈可能性と透明性のコンセプトを紹介します。デベロッパーとエンジニアにとって AI の透明性が重要であることについて説明します。データと AI モデルの両方で解釈可能性と透明性を達成できる実践的な方法とツールを検証します。

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このコースでは、責任ある AI および AI に関する原則のコンセプトを紹介します。AI / ML の実践における公平性とバイアスを特定し、バイアスを軽減するための実践的な手法を取り扱います。具体的には、Google Cloud プロダクトとオープンソース ツールを使用して責任ある AI のベスト プラクティスを実装するための実践的な方法とツールを検証します。

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生成 AI アプリケーションは、大規模言語モデル(LLM)の発明以前にはほぼ不可能であった、新しいユーザー エクスペリエンスを生み出すことができます。アプリケーション デベロッパーが Google Cloud 上で生成 AI を活用し、魅力的で強力なアプリを構築するにはどうすればよいでしょうか? このコースでは、生成 AI アプリケーションについて学びます。また、プロンプト設計と検索拡張生成(RAG)を使用して、LLM を活用した強力なアプリケーションを構築する方法についても学びます。さらに、生成 AI アプリケーションで使用できるプロダクション レディなアーキテクチャについて学び、LLM と RAG ベースのチャット アプリケーションを構築します。

詳細

このコースでは、ML の実務担当者に、生成 AI モデルと予測 AI モデルの両方を評価するための重要なツール、手法、ベスト プラクティスを身につけていただきます。モデル評価は、ML システムが本番環境で信頼性が高く、正確で、高性能な結果を確実に提供するための重要な分野です。 参加者は、さまざまな評価指標、方法論のほか、さまざまなモデルタイプやタスクにおけるそれらの適切な適用について理解を深めます。このコースでは、生成 AI モデルによってもたらされる固有の課題に重点を置き、それらの課題に効果的に取り組むための戦略を提供します。参加者は、Google Cloud の Vertex AI プラットフォームを活用して、モデルの選択、最適化、継続的なモニタリングのための堅牢な評価プロセスを実装する方法を学びます。

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 ML 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。

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このコースでは、生成 AI モデルのデプロイと管理において MLOps チームが直面する特有の課題に対処するために必要な知識とツールを提供し、AI チームが MLOps プロセスを合理化して生成 AI プロジェクトを成功させるうえで Vertex AI がどのように役立つかを説明します。

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