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。
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Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your 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 skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.
Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.
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This intermediate-level quest is unique among Qwiklabs quests. These labs have been curated to give operators hands-on practice with Anthos—a new, open application modernization platform on GCP. Anthos enables you to build and manage modern hybrid applications. Tasks include: installing service mesh, collecting telemetry, and securing your microservices with service mesh policies. This quest is composed of labs targeted to teach you everything you need to know to introduce service mesh, and Anthos, into your next hybrid cloud project.
Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on Google Cloud.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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大規模なコンピューティング能力を使用してパターンを認識し、 画像を「読み取る」ことは、自動運転車や顔認識に使用される AI の基盤技術の一つです 。 Google Cloud Platform は、 API を呼び出すだけで利用できるシステムを通じて、ワールドクラスの速度と精度を提供します。 こうした機能とさまざまな API を備えた GCP のツールを使えば、 ほぼあらゆる ML ジョブに対応できます。 この入門コースでは、 画像処理に用いられる ML の実践的な演習を行います。 ラボを活用して、画像にラベルを付けたり、顔やランドマークを検出したり、 画像内のテキストを抽出、分析、翻訳したりすることができます。
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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.
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ML は、IT 分野で最も急速に成長している技術の一つであり、Google Cloud Platform はその発展に大きく貢献してきました。 Google Cloud では多数の API により、ほぼすべての ML ジョブに対応するツールを提供しています。 この入門コースでは、ラボを通じて言語処理に活用できる ML の実践演習を行います。 これにより、テキストからのエンティティの抽出、 感情分析と構文解析、音声文字変換のための Speech-to-Text API の使用方法を学ぶことができます。
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クラウド アーキテクチャ: 設計、実装、管理 コースを修了して、スキルバッジを獲得しましょう。 Apache ウェブサーバーを使用した一般公開ウェブサイトのデプロイ、 起動スクリプトを使用した Compute Engine VM の構成、 Windows の踏み台インスタンスとファイアウォール ルールを使用したセキュアな RDP の構成、ビルドした Docker イメージの Kubernetes クラスタへのデプロイと更新、 CloudSQL インスタンスの作成と MySQL データベースのインポートといったスキルを実証できます。 このスキルバッジは、 Google Cloud Certified Professional Cloud Architect 認定資格試験に出題されるトピックを理解するのに 役立つリソースです。
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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
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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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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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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.
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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。
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…
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In this course you will learn how you to harness serious Google Cloud power and infrastructure. The hands-on labs will give you use cases and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your Google Cloud projects to the next level.
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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.
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Learn the ins and outs of Google Cloud's operations suite, 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. These labs 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. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.
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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.
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Happy Lunar New Year from Qwiklabs! Begin your new year with an exciting game full of fun and learning. Play this game and complete the labs from the Cloud Architecture Quest and get a headstart for your certification preps!
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Welcome, gamers! Over a billion: that's how many Google Assistant devices will be out in the world by the end of the year. Want in? Learn to build your own Google Assistant app and win points in today's Qwiklabs game. 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. Hurry, the game is open until Friday at midnight, EDT. Ready to play?
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セキュリティは、Google Cloud のサービスにおける妥協のない機能であり、これを念頭に、 プロジェクトをまたいで安全性を確保し ID を保護するための専用ツールが 開発されています。この入門コースでは、 ユーザー アカウントと仮想マシン アカウントの管理における主要機能である Google Cloud の Identity and Access Management（IAM）サービス の実践演習を行います。VPC と VPN のプロビジョニングを通してネットワーク セキュリティを実際に体験し、セキュリティ 脅威とデータ損失防止に使用できるツールについて学びます。
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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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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. 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 Python 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 Python applications straight away.
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Have you chosen your language for the 30-day challenge yet? Make progress towards completing the challenge + earning your badge in this week's game. Only a few days left until the challenge ends!
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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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Cloud Healthcare API bridges the gap between care systems and applications built on Google Cloud. By supporting standards-based data formats and protocols of existing healthcare technologies, Cloud Healthcare API connects your data to advanced Google Cloud capabilities, including streaming data processing with Cloud Dataflow, scalable analytics with BigQuery, and machine learning with Cloud Machine Learning Engine. In this Quest you will use the Cloud Healthcare API to ingest and process data in the industry standard FHIR, HL7v2 and DICOM formats, train a TensorFlow model for prediction with FHIR data, and also gain practice with de-identification of datasets.
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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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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 move to Google Cloud Platform (GCP) public cloud services is underway, and requirements for cloud security are real. Palo Alto Networks offers innovative and comprehensive protection as you adopt public cloud services. In today's game, get hands-on experience with how Palo Alto Networks solutions complement the native GCP security toolset, including network, host and cloud-native security delivered through APIs for comprehensive protection.
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How can artificial intelligence and machine learning benefit your business? Let Google Cloud do the hard work and start taking advantage of advanced AI and ML tools. Dive deep into key solutions to common use cases and gain hands-on experience with TensorFlow, forecasting and prediction, plus score points and compete with other players in today's game.
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Friday the 13th might be scary, but it doesn't have to be the day you get a surprise bill. Learn how to understand your GCP costs with a lab. In today's game, you will learn how to track and analyze your billing data. Bonus, complete these labs and you're only a few steps away from earning the "Understanding your GCP Costs" badge!
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You have data. We have analysis tools. Let's talk! In today's game, you will explore how Google Cloud can help you take advantage of the information you already have. Get hands-on practice with SQL, BigQuery and Data Studio, three tools we promise you will use again.
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How can artificial intelligence and machine learning benefit your business? Let Google Cloud do the hard work and start taking advantage of advanced AI and ML tools. Dive deep into key solutions to common use cases and gain hands-on experience with data processing, natural language processing, forecasting and prediction as well as scoring points and competing with other players in today's game.
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Welcome, gamers! Congratulations on completing the 30-day challenge and earning the Data Engineering badge. You're invited to put your new skills to the test and watch your name move on the leaderboard. (Hopefully upwards!) You might even be eligible for prizes: http://bit.ly/2lDV7RB
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In today's game, you will explore how Google Cloud can help you solve real-world challenges with different data tools, while making progress on the Data Engineering quest. Want to learn more about what data can do? Check out how the New York Times, Macy's and healthcare researchers are using tools like Kubernetes and Tensorflow: http://bit.ly/32e0bwi
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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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In today's game, you will explore the overlap between IoT and big data, while continuing to make progress on the Data Engineering quest. Start by familiarizing yourself with key IoT concepts then challenge yourself to build an IoT Analytics Pipeline. Put GCP to the test and explore key solutions to common use cases and gain hands-on experience with IoT data at scale, ETL processing and more, plus score points and compete with other players in today's game.
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。
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.
This quest of "Challenge Labs" gives the student preparing for the Google Cloud Certified Professional Cloud Architect certification hands-on practice with common business/technology solutions using Google Cloud architectures. Challenge Labs do not provide the "cookbook" steps, but require solutions to be built with minimal guidance, across many Google Cloud technologies. All labs have activity tracking, and in order to earn this badge you must score 100% in each lab. This quest is not easy and will put your Google Cloud technology skills to the test! Be aware that while practice with these labs will increase your knowledge and abilities, additional study, experience, and background in cloud architecture is recommended to prepare for this certification. Complete this quest to receive an exclusive Google Cloud digital badge.
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.
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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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.
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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。
Google Cloud での DevOps ワークフローの実装
Earned 3月 8, 2021 EST
Google Cloud での Kubernetes アプリケーションのデプロイ
Earned 3月 8, 2021 EST
安全な Google Cloud ネットワークの構築
Earned 3月 8, 2021 EST
[DEPRECATED] Build Interactive Apps with Google Assistant
Earned 3月 8, 2021 EST
Google Cloud Observability を使用したモニタリングとロギング
Earned 3月 7, 2021 EST
Google Cloud ネットワークの構築
Earned 3月 7, 2021 EST
Google Cloud でのクラウド セキュリティの基礎の実践
Earned 3月 7, 2021 EST
Google Cloud におけるアプリ開発環境の設定
Earned 3月 6, 2021 EST
Compute Engine での Cloud Load Balancing の実装
Earned 3月 6, 2021 EST
Getting Started with Go on Google Cloud
Earned 3月 6, 2021 EST
Anthos: Service Mesh
Earned 3月 6, 2021 EST
Firebase を使用したサーバーレス アプリの開発
Earned 3月 6, 2021 EST
Advanced ML: ML Infrastructure
Earned 3月 5, 2021 EST
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned 9月 13, 2020 EDT
ML 入門: 画像処理
Earned 9月 13, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned 9月 13, 2020 EDT
ML 入門: 言語処理
Earned 9月 10, 2020 EDT
クラウド アーキテクチャ: 設計、実装、管理
Earned 6月 24, 2020 EDT
DEPRECATED Applied Data: Blockchain
Earned 3月 29, 2020 EDT
機械学習API
Earned 3月 29, 2020 EDT
DEPRECATED IoT in the Google Cloud
Earned 3月 29, 2020 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned 3月 29, 2020 EDT
VM Migration
Earned 3月 29, 2020 EDT
Data Science on the Google Cloud Platform
Earned 3月 29, 2020 EDT
Google Cloud Run Serverless Workshop
Earned 3月 29, 2020 EDT
Google Cloud Solutions I: Scaling Your Infrastructure
Earned 3月 28, 2020 EDT
Deprecated Kubernetes Solutions
Earned 3月 28, 2020 EDT
DEPRECATED Google Cloud's Operations Suite
Earned 3月 28, 2020 EDT
Baseline: Deploy & Develop
Earned 3月 28, 2020 EDT
Cloud Hero: Lunar New Year Special
Earned 1月 26, 2020 EST
OK Google! Speedrun
Earned 11月 15, 2019 EST
セキュリティと ID の基礎
Earned 11月 15, 2019 EST
DEPRECATED Network Performance and Optimization
Earned 11月 14, 2019 EST
DEPRECATED Application Development - Python
Earned 11月 14, 2019 EST
Cloud Hero Speedrun: AppDev Challenge Game 2
Earned 10月 19, 2019 EDT
Cloud Development
Earned 10月 4, 2019 EDT
Cloud Healthcare API
Earned 10月 4, 2019 EDT
DevOps の基礎
Earned 10月 3, 2019 EDT
Cloud Hero: Smart Analytics
Earned 9月 28, 2019 EDT
Palo Alto Networks Game
Earned 9月 21, 2019 EDT
Cloud Hero: Artificial Intelligence and Machine Learning
Earned 9月 15, 2019 EDT
Cloud Hero Speedrun: Understanding Your GCP Costs
Earned 9月 13, 2019 EDT
Cloud Hero Speedrun: BigQuery for Data Analysis
Earned 9月 7, 2019 EDT
Cloud Hero Warm Up: Artificial Intelligence and Machine Learning
Earned 9月 5, 2019 EDT
30 Days of Data Challenge: Invitational Game
Earned 9月 5, 2019 EDT
Cloud Hero Speedrun: Data Solutions
Earned 8月 31, 2019 EDT
ML のための BigQuery
Earned 8月 27, 2019 EDT
Cloud Hero Speedrun: IoT & Big Data
Earned 8月 22, 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 8月 21, 2019 EDT
Google デベロッパー向け基礎
Earned 8月 21, 2019 EDT
ベースライン: データ、ML、AI
Earned 8月 21, 2019 EDT
ベースライン: インフラストラクチャ
Earned 8月 20, 2019 EDT
Google Cloud の Kubernetes
Earned 8月 20, 2019 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned 8月 20, 2019 EDT
BigQuery for Data Warehousing
Earned 8月 20, 2019 EDT
クラウド エンジニアリング
Earned 8月 20, 2019 EDT
Cloud Architecture - Design, Implement, and Manage
Earned 8月 20, 2019 EDT
Google Cloud の基礎
Earned 8月 19, 2019 EDT
DEPRECATED BigQuery for Data Analysis
Earned 8月 16, 2019 EDT
BigQuery for Marketing Analysts
Earned 8月 15, 2019 EDT
[DEPRECATED] Data Engineering
Earned 8月 15, 2019 EDT
Cloud Implementation Approach
Earned 6月 30, 2019 EDT
DEPRECATED Cloud Architecture
Earned 6月 17, 2019 EDT