DEPRECATED Websites and Web Applications
Earned 5月 18, 2020 EDT
Cloud Development
Earned 5月 16, 2020 EDT
ML 入門: 画像処理
Earned 5月 16, 2020 EDT
DEPRECATED Application Development - Python
Earned 5月 16, 2020 EDT
ML 入門: 言語処理
Earned 5月 13, 2020 EDT
ベースライン: データ、ML、AI
Earned 3月 19, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned 3月 19, 2020 EDT
[DEPRECATED] Data Engineering
Earned 3月 19, 2020 EDT
Compute & Networking
Earned 2月 19, 2020 EST
Solutions Architect - Associate
Earned 2月 19, 2020 EST
Cloud Logging
Earned 2月 19, 2020 EST
Corporate Apps on AWS for Windows
Earned 2月 18, 2020 EST
Security on AWS
Earned 2月 18, 2020 EST
Google Kubernetes Engine Best Practices
Earned 2月 16, 2020 EST
Understand Your Google Cloud Costs
Earned 2月 16, 2020 EST
VM Migration
Earned 2月 14, 2020 EST
クラウド エンジニアリング
Earned 1月 25, 2020 EST
ベースライン: インフラストラクチャ
Earned 1月 25, 2020 EST
DEPRECATED Cloud Architecture
Earned 1月 7, 2020 EST
Google Cloud Essentials
Earned 1月 7, 2020 EST
Google Cloud の Kubernetes
Earned 1月 6, 2020 EST
DevOps の基礎
Earned 12月 28, 2019 EST
Terraform を使用したクラウド インフラストラクチャの管理
Earned 12月 24, 2019 EST
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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これは2 つ目のクエストで、Google Cloud Platform の Valliappa Lakshmananが O'Reilly Media, Inc. から出版した「Data Science on the Google Cloud Platform」からの派生したラボです。9つのラボで構成され、1つ目のクエストで練習したスキルをさらに伸ばし、最先端で本格的な機械学習を実際的なデータで実行することで、Google Cloud Platformの機能とサービスを堪能していだけます。
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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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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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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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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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The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with Google Cloud.
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When it comes to hosting websites and web applications, you want a framework that’s robust, fast, and secure. By choosing the Google Cloud Platform, you will have all of those needs covered. In this fundamental-level quest, you will get hands-on practice with GCPs key infrastructure and computing services for the web. From deploying your first web app, to integrating Cloud SQL with Ruby on Rails, to mapping the NYC subway system on App Engine, you will learn all the skills needed to harness GCPs web hosting power.
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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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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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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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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。
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.
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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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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).
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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 – Associate Exam.
Visit AWS Certification to learn more about this exam and find more resources to prepare.
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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.
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Learn how to deploy Microsoft Windows Server-based applications in the AWS cloud, including Microsoft Exchange, Dynamics CRM and SharePoint.
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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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Get Anthos Ready. Demand for Google Kubernetes Engine is growing, and customers are looking to Google and its partners to provide in-depth technical knowledge. This first Google Kubernetes Engine-centric Quest of best practices hands-on labs will get you started containerizing to modernize in place , and then managing your deployed apps and services -- with monitoring, tracing, and logging.
詳細
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。
詳細
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。
Google Cloud Solutions I: Scaling Your Infrastructure
Earned 5月 23, 2020 EDT
Google Cloud Platformでのデータサイエンス：機械学習
Earned 5月 23, 2020 EDT
機械学習API
Earned 5月 23, 2020 EDT
Deprecated Kubernetes Solutions
Earned 5月 23, 2020 EDT
Advanced ML: ML Infrastructure
Earned 5月 22, 2020 EDT
Google Cloud Run Serverless Workshop
Earned 5月 21, 2020 EDT
[DEPRECATED] Deploying Applications
Earned 5月 20, 2020 EDT
DEPRECATED Websites and Web Applications
Earned 5月 18, 2020 EDT
Cloud Development
Earned 5月 16, 2020 EDT
ML 入門: 画像処理
Earned 5月 16, 2020 EDT
DEPRECATED Application Development - Python
Earned 5月 16, 2020 EDT
ML 入門: 言語処理
Earned 5月 13, 2020 EDT
ベースライン: データ、ML、AI
Earned 3月 19, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned 3月 19, 2020 EDT
[DEPRECATED] Data Engineering
Earned 3月 19, 2020 EDT
Compute & Networking
Earned 2月 19, 2020 EST
Solutions Architect - Associate
Earned 2月 19, 2020 EST
Cloud Logging
Earned 2月 19, 2020 EST
Corporate Apps on AWS for Windows
Earned 2月 18, 2020 EST
Security on AWS
Earned 2月 18, 2020 EST
Google Kubernetes Engine Best Practices
Earned 2月 16, 2020 EST
Understand Your Google Cloud Costs
Earned 2月 16, 2020 EST
VM Migration
Earned 2月 14, 2020 EST
クラウド エンジニアリング
Earned 1月 25, 2020 EST
ベースライン: インフラストラクチャ
Earned 1月 25, 2020 EST
DEPRECATED Cloud Architecture
Earned 1月 7, 2020 EST
Google Cloud Essentials
Earned 1月 7, 2020 EST
Google Cloud の Kubernetes
Earned 1月 6, 2020 EST
DevOps の基礎
Earned 12月 28, 2019 EST
Terraform を使用したクラウド インフラストラクチャの管理
Earned 12月 24, 2019 EST