Complete the Evaluate Gen AI model and agent performance skill badge to demonstrate your ability to use the Gen AI evaluation service. You will evaluate models to select the best model for a given task, compare models against each other and evaluate the performance of agents.
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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Evaluation is important at every step of your Gen AI development process. In this course you will learn how to evaluate gen AI agents built using agent frameworks.
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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。
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This course delves into the complexities of assessing the quality of large language model outputs. It examines the challenges enterprises face due to the subjective and sometimes incorrect nature of LLM responses, including hallucinations and inconsistent results. The course introduces various evaluation metrics for different tasks like classification, text generation, and question answering, such as Accuracy, Precision, Recall, F1 score, ROUGE, BLEU, and Exact Match. It also explores evaluation methods offered by Vertex AI LLM Evaluation Services, including computation-based, autorater, and human evaluation, providing insights into their application and benefits. Finally, the module covers how to unit test LLM applications within Vertex AI.
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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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Learn how to create Hybrid Search applications using Vertex AI Vertex Search to combine semantic searching with keyword search to return results based on both semantic meaning and keyword matching.
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Learn how to build your own Retrieval-Augmented Generation (RAG) solutions for greater control and flexibility than out-of-the-box implementations. Create a custom RAG solution using Vertex AI APIs, vector stores, and the LangChain framework.
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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。
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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts.
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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Generate engaging media with Google's foundation models for media. Create new images with Imagen, or edit your existing photos by adding details or outpainting to create a wider view. Replace backgrounds to put your products in new scenes. And learn the basics of generating videos with Veo!
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Complete the Develop solutions using Model Garden APIs skill badge to demonstrate your ability to use Vertex AI Model Garden features when building gen AI solutions. You will use partner APIs such as Anthropic Claude ands Meta Llama, deploy and programatically access foundation models like Gemma and Stable Diffusion XL and access Vertex AI Endpoints.
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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Model tuning is an effective way to customize large models to your tasks. It's a key step to improve the model's quality and efficiency. Model tuning provides benefits such as higher quality results for your specific tasks and increased model robustness. You learn some of the tuning options available in Vertex AI and when to use them.
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Model Garden is a model library that helps you discover, test, and deploy models from Google and Google partners. Learn how to explore the available models and select the right ones for your use case. And how to deploy and interact with Model Garden models through the Google Cloud console and APIs.
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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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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.
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このコースは、Vertex AI Notebooks に関する入門コースです。Vertex AI Notebooks は Jupyter ノートブックをベースとした環境であり、データの準備からモデルのデプロイとモニタリングに至るまで ML のワークフロー全体をサポートする統合プラットフォームを提供します。このコースでは、（1）Vertex AI Notebooks の種類とそれぞれの機能、（2）Vertex AI Notebooks の作成と管理の方法について説明します。
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このコースでは、Google Cloud の生成 AI を活用したコラボレーターである Gemini が、Google のプロダクトとサービスを使用してアプリケーションを開発、テスト、デプロイ、管理するうえでどのように役立つかを学習します。Gemini を利用して、ウェブ アプリケーションを開発および構築する方法、アプリケーションのエラーを修正する方法、テストを作成する方法、データをクエリする方法を学びます。ハンズオンラボでは、Gemini を使用することでソフトウェア開発ライフサイクル（SDLC）がどのように向上するかを体験します。
Duet AI は、次世代モデルである Gemini に名称変更されました。
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このコースでは、Google Cloud の生成 AI を活用したコラボレーターである Gemini が、エンジニアによるインフラストラクチャの管理にどのように役立つかについて学習します。アプリケーション ログを検索して理解するように Gemini に指示する方法、GKE クラスタを作成する方法、ビルド環境の作成方法を調査する方法を学びます。ハンズオンラボでは、Gemini を使用することで DevOps ワークフローがどのように向上するかを体験します。
Duet AI は、次世代モデルである Gemini に名称変更されました。
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このコースでは、予測 AI と生成 AI の両方のプロジェクトを構築できる、Google Cloud の AI および機械学習（ML）サービスについて紹介します。AI の基盤、開発、ソリューションを含むデータから AI へのライフサイクル全体で利用可能なテクノロジー、プロダクト、ツールについて説明するとともに、魅力的な学習体験と実践的なハンズオン演習を通じて、データ サイエンティスト、AI 開発者、ML エンジニアの方々がスキルや知識を強化できるようサポートすることを目指しています。
このコースでは、生成 AI を活用した Google Cloud のコラボレーターである Gemini が、顧客データの分析や商品売上の予測にどのように役立つかについて学びます。また、BigQuery で顧客データを使用して、新規顧客を特定、分類、発見する方法も学習します。ハンズオンラボでは、Gemini でデータ分析と ML のワークフローがどのように向上するかを体験します。
Duet AI は、次世代モデルである Gemini に名称変更されました。
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「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。 スキルバッジは、Google Cloud のプロダクトとサービスの習熟度を示す Google Cloud 発行の限定デジタルバッジで、 インタラクティブなハンズオン環境での知識の応用力を証明するものです。このスキル バッジ コースと最終評価チャレンジラボを修了し、スキルバッジを獲得して ネットワークで共有しましょう。
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このコースでは、Google Cloud の生成 AI を活用したコラボレーターである Gemini が、管理者によるインフラストラクチャのプロビジョニングにどのように役立つかについて学習します。Gemini にプロンプトを入力して、インフラストラクチャの説明、GKE クラスタのデプロイ、既存のインフラストラクチャの更新についての情報を取得する方法を学びます。ハンズオン ラボでは、Gemini を使用することで GKE のデプロイ ワークフローがどのように向上するかを体験します。
Duet AI は、Google の次世代モデルである Gemini に名称変更されました。
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Prompts are essential for guiding a Gen AI model to generate relevant and desired content. Start GenAIus conversations and earn a Google Cloud credential! No prior experience required!
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このコースでは、生成 AI を活用した Google Cloud のコラボレーター、Gemini が、デベロッパーのアプリケーション構築にどのように役立つかについて学びます。コードの説明、Google Cloud サービスの提案、アプリケーションのコード生成を Gemini に指示する方法について学びます。ハンズオンラボを使用して、Gemini でアプリケーション開発ワークフローがどのように向上するかを体験します。
Duet AI は、次世代モデルである Gemini に名称変更されました。
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Gen AI is leading the charge in reshaping the digital landscape. Whether you're a seasoned professional or a newcomer to the field, exploring Vertex AI opens doors to new possibilities, and obtaining a Google Cloud credential in this innovative technology can set you apart in the job market. Best part? No prior experience required.
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Hey there! You're invited to game on with Qwiklabs Trivia for October 2023! Play throughout the month and boost your cloud learning journey. This week, we're releasing a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the October week 4 badge!
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Hey there! You're invited to game on with Qwiklabs Trivia for October 2023! Play throughout the month and boost your cloud learning journey. This week, we're releasing a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the October week 3 badge!
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'As businesses of all sizes move their operations to the cloud, the demand for cloud talent continues to grow. Want to be part of that talent pool? Game on to get familiar with data analysis and serverless technologies, and get your hands on a Google Cloud Credential that can help you stand out to potential employers. No prior experience required.'
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Hey there! You're invited to game on with Qwiklabs Trivia for October 2023! Play throughout the month and boost your cloud learning journey. This week, we're releasing a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the October week 2 badge!
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Hey there! You're invited to game on with Qwiklabs Trivia for October 2023! Play throughout the month and boost your cloud learning journey. This week, we're releasing a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the October week 1 badge!
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As employers increasingly seek data experts on a global scale to solve real-world problems, we want you to stay ahead of the curve by acquiring the latest and most in-demand data skills. Game on to showcase your talent to the world by earning your first Google Cloud Credential!
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Welcome to Qwiklabs Trivia for September! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the September badge.
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Earn the intermediate skill badge by completing the Perform Predictive Data Analysis in BigQuery course, where you will gain practical experience on the fundamentals of sports data science using BigQuery, including how to create a soccer dataset in BigQuery by importing CSV and JSON files; harness the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on the soccer event data, and evaluate the impressiveness of World Cup goals.
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The beautiful game is changing, and data science is playing a big role. Teams are now using data to make better decisions about everything, from player recruitment to game strategy. We invite you to get hands-on experience on the fundamentals of sports data science no matter who you're cheering for! Use BigQuery ML to train advanced models to predict goals and evaluate performance. Learn new skills and get started towards earning your first Google Cloud Credential. No prior experience required.
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For organisations to thrive in the digital world, it is important for them to have secured networks to protect sensitive data, prevent cyber threats and maintain customer trust. Learn the principles of network design, security and management and integrating BigQuery Data and Google Workspace using Apps Script. Gain hands-on experience with labs carefully designed to nurture and assess your tech skills and set you on a course to earn your first Google Cloud credential.
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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!
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The world around us is changing and mastering future-driven technologies is the key to success. We want you to get started by learning a little of everything! Discover machine learning in data analysis, build scalable cloud solutions and accelerate software development that will shape the future. The possibilities in the Arcade are endless and all of those will lead you towards earning your first Google Cloud Credential. No prior experience required.
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The demand for data skills is growing rapidly, and we want you to get some of that sweet knowledge! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. Data can be used to identify trends, patterns, and insights that can help businesses improve their operations, products, and services - which makes data career paths highly valuable. There are a lot of different aspects to data science, so it's important to start with the basics - and we’ve got you covered. Kickstart your data skills discovery and get hands-on experience in the Arcade, with labs that help you learn and earn your first Google Cloud credential. No experience required.
Description: According to IDC, by 2026, 7 PB of data will be generated per second globally. But what you *do* with the data is what matters. Data is the heart of digital transformation and offers incredible opportunities for organizations to accelerate the most strategic business outcomes, like revenue and productivity. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud's powerful data tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.
Complete the Analyze BigQuery Data in Connected Sheets skill badge to demonstrate that you can use Connected Sheets to access, analyze, visualize, and share billions of rows of BigQuery data from your Google Sheets spreadsheet.
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More than 90% of IT leaders say they're looking to grow their cloud environments in the next several years, yet more than 80% of those same leaders identified a lack of skills as a barrier to growth. This means that tech skills (particularly cloud skills!) are in high demand. Want to grow your skills and take advantage of the opportunity? Play now to get hands-on experience with Google Cloud. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential. No experience required.
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This challenge lab tests your skills and knowledge from the labs in the Monitor and Manage Google Cloud Resources quest. You should be familiar with the content of labs before attempting this lab.
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Welcome Gamers! Explore the power of machine learning by using multiple machine learning APIs together, all while having fun! Translate the text with the Translation API and analyze it with the Natural Language API. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.
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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Earn points by completing the labs accurately and receive bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.
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This quest offers hands-on practice with Cloud Data Fusion, a cloud-native, code-free, data integration platform. ETL Developers, Data Engineers and Analysts can greatly benefit from the pre-built transformations and connectors to build and deploy their pipelines without worrying about writing code. This Quest starts with a quickstart lab that familiarises learners with the Cloud Data Fusion UI. Learners then get to try running batch and realtime pipelines as well as using the built-in Wrangler plugin to perform some interesting transformations on data.
Firebase is a backend-as-service (Bass) platform for creating mobile and web applications. In this quest you will learn to build serverless web apps, import data into a serverless database, and build a Google Assistant application with Firebase and its Google Cloud integrations. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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Google Cloud で VM の移行を行う場合、定義済みかつユーザーが実行できる再現性のある方法が用意されています。このクエストでは、4 つのステップで構成される移行手順で実践演習を行います。CloudPhysics で評価レポートを作成し、Terraform の Infrastructure as Code のテンプレートを活用し、CloudEndure でリフト＆シフトの移行を実行し、最後にクラウド ネイティブのワークロードとしてアプリケーションを複製します。このクエストに登録し、VM 移行用の Google の最新のソリューション セットで練習しましょう。さらに、Google Kubernetes Engine の基礎的なラボも含まれており、受講者は手順を再確認することができます。
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If you want to take your Google Cloud networking skills to the next level, look no further. This course is composed of labs that cover real-life use cases and it will teach you best practices for overcoming common networking bottlenecks. From getting hands-on practice with testing and improving network performance, to integrating high-throughput VPNs and networking tiers, Network Performance and Optimization is an essential course for Google Cloud developers who are looking to double down on application speed and robustness.
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安全な Google Cloud ネットワークの構築コースを修了してスキルバッジを獲得しましょう。このコースでは、Google Cloud でアプリケーションを ビルド、スケール、保護するための複数のネットワーク関連リソースについて学習します。 スキルバッジは、Google Cloud のプロダクトとサービスの習熟度を示す Google Cloud 発行の限定デジタルバッジです。 インタラクティブなハンズオン環境での知識の応用力を証明するものです。スキルバッジと 最終評価チャレンジラボを完了し、デジタルバッジを獲得して ネットワークで共有しましょう。
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In this quest, you will learn about Google Cloud’s IoT Core service and its integration with other services like GCS, Dataprep, Stackdriver and Firestore. The labs in this quest use simulator code to mimic IOT devices and the learning here should empower you to implement the same streaming pipeline with real world IoT devices.
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You work at a startup and you’re 6 weeks away from launching your new product. It’s a game changer and sure to land successfully, but your company needs to run lean between now and launch day. Everyone is pitching in to be smart and control costs.That’s where today’s game begins. See which team can save the most money through cost optimization. Each lab in this game walks you through a particular GCP tool that helps you monitor and optimize your spend. The points you score individually as you complete each lab will add up to your team’s total! Join the game, then join a team by updating your player name and avatar. At the end of the game, we’ll total all the points for both teams and declare a winning team. Every player on the winning team will receive 50 free Qwiklabs credits.
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This course offers hands-on practice with migrating MySQL data to Cloud SQL using Database Migration Service. You start with an introductory lab that briefly reviews how to get started with Cloud SQL for MySQL, including how to connect to Cloud SQL instances using the Cloud Console. Then, you continue with two labs focused on migrating MySQL databases to Cloud SQL using different job types and connectivity options available in Database Migration Service. The course ends with a lab on migrating MySQL user data when running Database Migration Service jobs.
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Earn a skill badge by completing the Secure Workloads in Google Kubernetes Engine quest, where you learn about security at scale on Google Kubernetes Engine (GKE) including how to: migrate containers from virtual machines to Google Kubernetes Engine, restrict network connections in GKE using firewalls and Network Policies, use role-based access controls (RBAC) in GKE, use Binary Authorization for security controls of your images, secure applications in GKE using 3 access levels: host, network, Kubernetes API, and harden GKE cluster configurations. 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 this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 8 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.
Cloud Dataprep by Trifacta is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis. In today's game, get hands-on experience with the Cloud Dataprep UI. Learn how to create a data transformation pipeline, automate the data pipeline and much more with Cloud Dataprep and BigQuery.
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Google Cloud での DevOps ワークフローの実装 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、 Cloud Source Repositories を使用した Git リポジトリの作成、 Google Kubernetes Engine（GKE）上でのデプロイのリリース、管理、スケール、 コンテナ イメージのビルドと GKE へのデプロイを自動化する CI / CD パイプラインの設計といったスキルを実証できます。 スキルバッジは、Google Cloud のプロダクトとサービスの習熟度を示す Google Cloud 発行の限定デジタルバッジで、 インタラクティブなハンズオン環境での知識の応用力を証明するものです。このスキル バッジ コースと最終評価チャレンジラボを完了し、スキルバッジを獲得して ネットワークで共有しましょう。
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In this fundamental-level course, you will learn the ins and outs of Google Cloud's operations suite running on Google Kubernetes Engine, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. The labs in this course will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials course. Additional lab experience with the labs in the Baseline - Infrastructure course will also be useful. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the additional challenge lab at the end of this course to receive an exclusive Google Cloud digital badge.
「Google Cloud ネットワークの構築」コースを修了してスキルバッジを獲得しましょう。このコースでは、 アプリケーションをデプロイしてモニタリングするための複数の方法について学びます。具体的には、IAM ロールの確認とプロジェクト アクセスの追加 / 削除、 VPC ネットワークの作成、Compute Engine VM のデプロイとモニタリング、 SQL クエリの記述、Compute Engine での VM のデプロイとモニタリング、Kubernetes を使用した複数のデプロイ アプローチによるアプリケーションのデプロイなどです。 スキルバッジは、 Google Cloud のプロダクトとサービスの習熟度を示す Google Cloud 発行の限定デジタルバッジです。 インタラクティブなハンズオン環境で 知識の応用力が試されます。このスキルバッジと 最終評価チャレンジラボを完了し、スキルバッジを獲得して ネットワークで共有しましょう。
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DevOps によって 競争優位性を確保します。DevOps とは、ソフトウェア デリバリーを迅速化し、サービスの信頼性を向上させ、 ソフトウェアの開発と運用に影響を与えるステークホルダーの間で共有の当事者意識を高めることを目的とする、組織的、 文化的な考え方や取り組みです。このクエストでは、Google Cloud を使用して ソフトウェア デリバリーの速度、安定性、可用性、安全性を向上させる方法を学びます。 DevOps Research and Assessment チームが Google Cloud に加わりました。自社の DevOps チームの実力はいかがですか？ 5 問の多肢選択式テストで評価してみましょう。
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「Google Cloud におけるアプリ開発環境の設定」コースを完了すると、スキルバッジを獲得できます。このコースでは、 Cloud Storage、Identity and Access Management、Cloud Functions、Pub/Sub のテクノロジーの基本機能を使用して、ストレージ中心のクラウド インフラストラクチャを構築し接続する方法を学びます。 スキルバッジは、Google Cloud のプロダクトとサービスの習熟度を示す Google Cloud 発行の限定デジタルバッジです。 インタラクティブなハンズオン環境で知識の応用力が試されます。このスキルバッジと最終評価チャレンジラボを完了し、スキルバッジを獲得してネットワークで共有しましょう。
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「Cloud Run でのサーバーレス アプリケーションの開発」コースの中級スキルバッジを獲得すると、 データ マネジメントのための Cloud Run と Cloud Storage の統合、 Cloud Run と Pub/Sub を使用した復元力のある非同期システムの構築、 Cloud Run を使用した REST API ゲートウェイの構築、Cloud Run でのサービスの構築とデプロイといったスキルを実証できます。 スキルバッジは、Google Cloud のプロダクトとサービスの習熟度を示す Google Cloud 発行の限定デジタルバッジです。 インタラクティブなハンズオン環境での知識の応用力を証明するものです。このスキル バッジ コースと最終評価チャレンジラボを完了し、スキルバッジを獲得して ネットワークで共有しましょう。
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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google…
Organizations around the world rely on Apache Kafka to integrate existing systems in real time and build a new class of event streaming applications that unlock new business opportunities. Google and Confluent are in a partnership to deliver the best event streaming service based on Apache Kafka and to build event driven applications and big data pipelines on Google Cloud Platform. In this course, you will first learn how to deploy and create a streaming data pipeline with Apache Kafka, then try out the different functionalities of the Confluent Platform.
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Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.
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このクエストは、技術または財務の担当者で GCP の費用の管理を担う方に最適です。請求先アカウントを設定する方法、リソースを整理する方法、請求アクセス権限を管理する方法について学習します。ハンズオンラボでは、請求書を表示する方法、請求レポートを使用して GCP の費用を追跡する方法、BigQuery や Google スプレッドシートを使用して請求データを分析する方法、データポータルを使用してカスタムの請求ダッシュボードを作成する方法について学習します。
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Serverless architectures allow you to build and run applications and services without needing to provision, manage, and scale infrastructure. This quest will show how to design, build, and deploy interactive serverless web applications, using a simple HTML/JavaScript web interface which uses Amazon API Gateway calls to send requests to AWS Lambda backends that query Amazon DynamoDB data.
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In this Quest, you will learn how to write functions with the AWS Lambda Service that respond to events and integrate other AWS Services. You will create applications that write records to Amazon DynamoDB, send messages with Amazon SNS, and monitor events in Amazon CloudWatch and external services. You will even write a back-end function in Lambda for creating a voice-response app for Alexa and the Amazon Echo.
詳細
この入門レベルのコースでは、アプリケーション開発者を対象に、Google Cloud のエコシステムを使用して安全、スケーラブル、インテリジェントなクラウドネイティブ アプリケーションを構築する方法を説明 します。インフラストラクチャの設定を行わずにアプリケーションの開発やスケーリングを行う方法、 データ分析を実施する方法、データから分析情報を得る方法、トレーニング済み ML の API を使って開発し、ML のエキスパートでなくても ML を活用する方法を学びます。 また、さまざまな Google サービスや API とのシームレスな統合を利用して、 インテリジェントなアプリを作成します。
詳細
Welcome to Cloud Hero, Gamers! Click "Join this Game". To modify your player name or avatar, go to your My Account page at https://google.qwiklabs.com. Points are earned by completing the steps in the lab.... and bonus points are earned for speed! Be sure to complete each lab by selecting the END option to get the maximum points. Please respect the GCP resource quotas that have been allocated. Otherwise, you'll waste your Game time and gain fewer points.
詳細
Welcome Gamers, Here's a fun opportunity for you to get yourself familiarized with Isitio. Earn the most points by completing the steps in the lab....and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. Challenge yourself to complete each task as quickly and accurately as possible to score points and earn badges!
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Have fun with this interesting game and get some hands on Stackdriver, Docker and Python. Challenge yourself to complete each task as quickly and accurately as possible to score points and earn badges!
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For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.
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Are you getting the most out of your data? Take advantage of the business insights you already have with the power of Google Cloud's analysis tools. Dive deep into key solutions to common use cases and gain hands-on experience with Data Studio, BigQuery and more data tools, plus score points and compete with other players in today's game.
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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.
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SQL だけを使用して、数時間ではなく数分で ML モデルを構築したいとお考えの場合、BigQuery ML は、データ アナリストが既存の SQL ツールやスキルを使って、ML モデルを作成、トレーニング、 評価し、そのモデルで予測を行うことを可能にして、ML をより多くの人が利用できるようにします。 この一連のラボでは、さまざまなモデルタイプを試して、 優れたモデルを作成する方法を学習します。
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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.
Welcome to Cloud Adoption Strategies Click "Join this Game".
To modify your player name or avatar, go to your My Account page at https://google.qwiklabs.com.
Points are earned by completing the steps in the lab.... and bonus points are earned for speed! Be sure to complete each lab by selecting the END option to get the maximum points.
Please respect the GCP resource quotas that have been allocated. Otherwise, you'll waste your Game time and gain fewer points.
詳細
Welcome to Cloud Implementation Approach! Click "Join this Game".
To modify your player name or avatar, go to your My Account page at https://google.qwiklabs.com.
Points are earned by completing the steps in the lab.... and bonus points are earned for speed! Be sure to complete each lab by selecting the END option to get the maximum points.
Please respect the GCP resource quotas that have been allocated. Otherwise, you'll waste your Game time and gain fewer points.
Welcome, gamers!
Are you figuring out how to use different Google tools available out there? Interested in Cryptocurrency? Here is a great opportunity to enjoy and get familiar with some cool Google tools. In today's game, rent a VM, ingest and analyse data, build an IoT pipeline, play with TensorFlow and then get the best out of this game by tracking Cryptocurrency with GCP in Real-Time!! Complete the game labs one by one to score points. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge. The top 10 players get 25 free Qwiklabs credits. And the winner? Eligible to receive an amazing E-Book `Data Science on Google Platform` by the Data Scientist Valliappa Lakshmanan. Hurry, the game is open for 24 hours only.
Ready to play?
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Achieving AWS Certification requires hands-on experience. This quest helps you get hands-on practice with several key services as you prepare for the AWS Certified SysOps Administrator - Associate Exam. Visit AWS Certification to learn more about this exam and find more resources to prepare.
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In this Quest, you will delve deeper into the uses and capabilities of Amazon Redshift. You will use a remote SQL client to create and configure tables, and gain practice loading large data sets into Redshift. You will explore the effects of schema variations and compression. You will explore visualization of Redshift data, and connect Redshift with Amazon Machine Learning to create a predictive data model.
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Want to learn the core SQL and visualization skills of a Data Analyst? Interested in how to write queries that scale to petabyte-size datasets? Take the BigQuery for Analyst Quest and learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.
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Welcome to DevZone Quest, a set of labs to deepen your understanding of the technology behind the Cloud Showcase Experiments featured in the Google Cloud Next 2019 San Francisco DevZone.
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In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.
Scientists, developers, and other technologists from many different industries are taking advantage of AWS to perform big data analytics and meet the challenges of the increasing volume, variety, and velocity of digital information. AWS offers a portfolio of cloud computing services to help you manage big data by reducing costs, scaling to meet demand, and increasing the speed of innovation. In this quest, you’ll learn to work with advanced services for Big Data.
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In this quest, you’ll learn to work with services related to Deployment and Management, including AWS Identity and Access Management (IAM), AWS Elastic Beanstalk, AWS CloudFormation, and AWS OpsWorks.
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This quest is designed to teach you how to apply AWS Identity and Access Management, in concert with several other AWS Services, to address real-world application and service security management scenarios.
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In this Quest, you’ll learn to work with services related to Storage and Content Delivery Networks, including Amazon Simple Storage Service (S3), Amazon Elastic Block Store (EBS), and Amazon CloudFront.
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Achieving AWS Certification requires hands-on experience. This quest helps you get hands-on practice with several key services as you prepare for the AWS Certified Solutions Architect – Professional Exam. Visit AWS Certification to learn more about this exam and find more resources to prepare.
詳細
Achieving AWS Certification requires hands-on experience. This quest helps you get hands-on practice with several key services as you prepare for the AWS Certified Solutions Architect – Associate Exam.
Visit AWS Certification to learn more about this exam and find more resources to prepare.
詳細
機械学習はもっとも迅速に成長しているテクノロジーの分野です。Google Cloud Platformは、その成長に一役かっています。APIのホストを使うことにより、GCPにはツールがあります。この上級レベルのクエストでは、「Implementing an AI Chatbot with Dialogflow」や「Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API」と同様に機械学習APIについてハンズオンで演習ができます。
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Google Cloud Application Programming Interfaces は、Google Cloud Services とプログラムでインタラクトするメカニズムです。このクエストは、GCP API のハンズオン演習を提供し、APIをブラウズして、実行するツールである Google の API Explorerを通して学習します。クラウドのストレージ間でのデータ移行の方法、コンピュートエンジンインスタンスのデプロイ、Dataprocクラスタの設定などを学ぶことにより、API が強力で、なぜGCPユーザが使用しているかを理解できます。
詳細
In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Java. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Java applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Java applications straight away.
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In this quest, you’ll learn to work with services related to Compute and Networking, including Amazon EC2, Amazon Elastic Load Balancing, and Amazon Virtual Private Cloud (VPC).
詳細
この基礎レベルの クエスト は他の Qwiklabs 製品の中でもユニークです。これらのラボは、Google Cloud Certified Professional Cloud Architect 認定資格試験に出題されるトピックやサービスについて、 IT プロフェッショナルがハンズオンで演習するために作成されました。 IAM からネットワーキング、Kubernetes engine のデプロイまで、Goodle Cloud の知識が試される特定のラボで構成されています。これらのラボでの演習は スキルや能力の向上に役立ちますが、試験ガイドやその他の対策資料も参照することをお勧めします。
In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
詳細
これは、Google Cloud Essentials よりもレベルの高い内容の練習機会を求めている初心者のクラウド デベロッパーに おすすめのコースです。Cloud Storage だけでなく、 Monitoring や Cloud Run functions などの主要なアプリケーション サービスに関連するラボを通して、 実践的な経験を積むことが可能です。また、 あらゆる Google Cloud イニシアチブに応用できる有益なスキルを身に付けることができます。
Evaluate Gen AI model and agent performance
Earned 8月 15, 2025 EDT
Evaluate ADK Agents with Vertex AI Gen AI Evaluation Service
Earned 8月 15, 2025 EDT
Vertex AI を使用した ML オペレーション（MLOps）: モデルの評価
Earned 8月 15, 2025 EDT
Model evaluation on Vertex AI
Earned 8月 15, 2025 EDT
Deploy a RAG application with vector search in Firestore
Earned 8月 15, 2025 EDT
Implement Hybrid Search
Earned 8月 11, 2025 EDT
Implement RAG with Vertex AI
Earned 8月 10, 2025 EDT
エンベディング作成、ベクトル検索、BigQuery での RAG
Earned 8月 5, 2025 EDT
Edit images with Imagen
Earned 8月 5, 2025 EDT
Generate and Edit Media with Imagen, Gemini, and Veo
Earned 8月 4, 2025 EDT
Build Gen AI solutions using Model Garden models and APIs
Earned 8月 4, 2025 EDT
Improve Performance by Fine-Tuning Foundation Models
Earned 8月 4, 2025 EDT
Find, Explore and Deploy Model Garden Models
Earned 8月 4, 2025 EDT
Extend Gemini with controlled generation and Tool use
Earned 7月 28, 2025 EDT
Empower Gen AI apps with tool use
Earned 7月 28, 2025 EDT
Vertex AI でノートブックを使用する
Earned 5月 8, 2025 EDT
エンドツーエンドの SDLC のための Gemini
Earned 5月 8, 2025 EDT
DevOps エンジニア向けの Gemini
Earned 5月 8, 2025 EDT
Google Cloud における AI と ML の概要
Earned 5月 6, 2025 EDT
Professional Machine Learning Engineer 学習ガイド
Earned 4月 3, 2025 EDT
Gemini Code Assist でアプリ開発を効率化する
Earned 3月 26, 2025 EDT
Google Cloud におけるロギングとモニタリング
Earned 6月 19, 2024 EDT
セキュリティ エンジニア向けの Gemini
Earned 4月 25, 2024 EDT
Google Cloud ネットワークの構築
Earned 4月 25, 2024 EDT
ネットワーク エンジニア向けの Gemini
Earned 4月 16, 2024 EDT
Google Cloud における Terraform を使用したインフラストラクチャの構築
Earned 4月 16, 2024 EDT
Compute Engine でのロード バランシングの実装
Earned 4月 10, 2024 EDT
データ サイエンティストとアナリスト向けの Gemini
Earned 4月 3, 2024 EDT
BigQuery ML を使用した ML モデルの作成
Earned 2月 29, 2024 EST
クラウド アーキテクト向けの Gemini
Earned 2月 22, 2024 EST
Level 3: GenAIus Conversations
Earned 2月 8, 2024 EST
アプリケーション開発者向けの Gemini
Earned 2月 5, 2024 EST
Level 3: GenAIus Vertex
Earned 1月 30, 2024 EST
Qwiklabs Trivia October 2023 Week 4
Earned 10月 24, 2023 EDT
Qwiklabs Trivia October 2023 Week 3
Earned 10月 23, 2023 EDT
Level 1: Data Analysis and Serverless Technologies
Earned 10月 23, 2023 EDT
Qwiklabs Trivia October 2023 Week 2
Earned 10月 13, 2023 EDT
Qwiklabs Trivia October 2023 Week 1
Earned 10月 13, 2023 EDT
Level 2: BigQuery and BigLake Data Skills
Earned 9月 29, 2023 EDT
Qwiklabs Trivia September 2023
Earned 9月 28, 2023 EDT
Perform Predictive Data Analysis in BigQuery
Earned 9月 24, 2023 EDT
Level 1: Sports Data
Earned 9月 24, 2023 EDT
Level 2: Apps Script and Networks
Earned 8月 30, 2023 EDT
Level 3: GenAI
Earned 8月 29, 2023 EDT
Level 1: BigQuery ML, Cloud Architecture and Devops Skills
Earned 8月 26, 2023 EDT
Level 1: Data with Google Cloud
Earned 6月 23, 2023 EDT
Dataplex を使ってみる
Earned 6月 22, 2023 EDT
ストリーミング分析を BigQuery に読み込む
Earned 5月 28, 2023 EDT
Level 2: Data Exploration with Looker, BigQuery and Sheets
Earned 5月 10, 2023 EDT
Looker ダッシュボードとレポート用にデータを準備する
Earned 5月 9, 2023 EDT
Analyze BigQuery Data in Connected Sheets
Earned 5月 9, 2023 EDT
Level 1: Managing Resources and Data in the Cloud
Earned 4月 19, 2023 EDT
Monitor and Manage Google Cloud Resources
Earned 4月 18, 2023 EDT
ML API Skills
Earned 4月 1, 2023 EDT
Cloud Hero BigQuery Skills
Earned 4月 1, 2023 EDT
Building Codeless Pipelines on Cloud Data Fusion
Earned 9月 9, 2021 EDT
Firebase を使用したサーバーレス アプリの開発
Earned 8月 25, 2021 EDT
Build Apps & Websites with Firebase
Earned 8月 12, 2021 EDT
VM Migration
Earned 8月 2, 2021 EDT
DEPRECATED Network Performance and Optimization
Earned 8月 1, 2021 EDT
安全な Google Cloud ネットワークの構築
Earned 7月 28, 2021 EDT
DEPRECATED IoT in the Google Cloud
Earned 7月 27, 2021 EDT
Save the Day!
Earned 7月 23, 2021 EDT
Migrating MySQL data to Cloud SQL using Database Migration Service
Earned 7月 22, 2021 EDT
[DEPRECATED] Secure Workloads in Google Kubernetes Engine
Earned 6月 29, 2021 EDT
Google Kubernetes Engine の費用の最適化
Earned 6月 28, 2021 EDT
Deprecated Kubernetes Solutions
Earned 6月 19, 2021 EDT
Google Kubernetes Engine のベスト プラクティス: セキュリティ
Earned 6月 19, 2021 EDT
Google Cloud での Kubernetes アプリケーションのデプロイ
Earned 6月 3, 2021 EDT
Dataprep by Trifacta Game on Google Cloud
Earned 5月 21, 2021 EDT
Google Cloud での DevOps ワークフローの実装
Earned 4月 23, 2021 EDT
DEPRECATED Google Cloud's Operations Suite on GKE
Earned 4月 19, 2021 EDT
Google Cloud における Terraform を使用したインフラストラクチャの構築
Earned 4月 16, 2021 EDT
Google Cloud ネットワークの構築
Earned 4月 14, 2021 EDT
DevOps の基礎
Earned 4月 13, 2021 EDT
Google Cloud におけるアプリ開発環境の設定
Earned 4月 8, 2021 EDT
Cloud Run でのサーバーレス アプリケーションの開発
Earned 4月 7, 2021 EDT
Google Cloud Run Serverless Workshop
Earned 4月 3, 2021 EDT
Compute Engine でのロード バランシングの実装
Earned 4月 2, 2021 EDT
Getting Started with Apache Kafka and Confluent Platform on Google Cloud
Earned 3月 20, 2021 EDT
Data Catalog Fundamentals
Earned 3月 12, 2021 EST
Understand Your Google Cloud Costs
Earned 3月 9, 2021 EST
Serverless Web Apps using Amazon DynamoDB
Earned 3月 1, 2021 EST
Serverless Design with AWS Lambda
Earned 2月 26, 2021 EST
Google デベロッパー向け基礎
Earned 2月 20, 2021 EST
Migrating Virtual Machines
Earned 9月 23, 2020 EDT
Cloud Hero: Application Development Proficient
Earned 12月 8, 2019 EST
Cloud Hero: Application Development
Earned 12月 6, 2019 EST
Using the Cloud SDK Command Line
Earned 11月 17, 2019 EST
Cloud Hero: Smart Analytics
Earned 10月 28, 2019 EDT
Cloud Development
Earned 10月 19, 2019 EDT
ML のための BigQuery
Earned 9月 21, 2019 EDT
[DEPRECATED] Data Engineering
Earned 8月 29, 2019 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned 8月 29, 2019 EDT
BigQuery for Marketing Analysts
Earned 8月 28, 2019 EDT
Cloud SQL
Earned 7月 7, 2019 EDT
BigQuery for Data Warehousing
Earned 7月 5, 2019 EDT
Cloud Adoption Strategies
Earned 7月 1, 2019 EDT
Cloud Implementation Approach
Earned 6月 26, 2019 EDT
クラウド エンジニアリング
Earned 6月 19, 2019 EDT
Data Science on the Google Cloud Platform
Earned 6月 16, 2019 EDT
Friday Speedrun: Machine Learning
Earned 6月 15, 2019 EDT
SysOps Administrator - Associate
Earned 6月 11, 2019 EDT
Advanced Operations Using Amazon Redshift
Earned 6月 11, 2019 EDT
DEPRECATED BigQuery for Data Analysis
Earned 5月 26, 2019 EDT
DevZone Quest
Earned 5月 18, 2019 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned 5月 5, 2019 EDT
Google Cloud ネットワークにおけるデプロイの自動化とトラフィックの管理
Earned 4月 20, 2019 EDT
Big Data on AWS
Earned 4月 14, 2019 EDT
Deployment & Management
Earned 4月 13, 2019 EDT
Security on AWS
Earned 4月 7, 2019 EDT
Storage & CDN
Earned 4月 6, 2019 EDT
Solutions Architect - Professional
Earned 4月 4, 2019 EDT
Solutions Architect - Associate
Earned 4月 3, 2019 EDT
機械学習API
Earned 3月 30, 2019 EDT
Exploring APIs
Earned 3月 24, 2019 EDT
DEPRECATED Application Development - Java
Earned 3月 23, 2019 EDT
Compute & Networking
Earned 3月 17, 2019 EDT
DEPRECATED Cloud Architecture
Earned 3月 17, 2019 EDT
Google Cloud の Kubernetes
Earned 3月 12, 2019 EDT
セキュリティと ID の基礎
Earned 3月 8, 2019 EST
ベースライン: データ、ML、AI
Earned 3月 5, 2019 EST
Baseline: Deploy & Develop
Earned 3月 4, 2019 EST
ベースライン: インフラストラクチャ
Earned 3月 1, 2019 EST
Google Cloud Essentials
Earned 2月 28, 2019 EST