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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「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。
「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、Dataproc 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。 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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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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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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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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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。
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.
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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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 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.
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.
DEPRECATED Applied Data: Blockchain
Earned 2月 9, 2021 EST
BigQuery ML を使用した ML モデルの作成
Earned 12月 30, 2020 EST
BigQuery のデータから分析情報を引き出す
Earned 12月 30, 2020 EST
Google Cloud の ML API 用にデータを準備
Earned 12月 30, 2020 EST
Deprecated Kubernetes Solutions
Earned 12月 30, 2020 EST
Baseline: Deploy & Develop
Earned 12月 3, 2020 EST
NCAA® March Madness®: Bracketology with Google Cloud
Earned 11月 25, 2020 EST
ML のための BigQuery
Earned 11月 25, 2020 EST
BigQuery でデータ ウェアハウスを構築する
Earned 11月 24, 2020 EST
DEPRECATED BigQuery for Data Analysis
Earned 11月 24, 2020 EST
BigQuery for Data Warehousing
Earned 11月 24, 2020 EST
セキュリティと ID の基礎
Earned 11月 24, 2020 EST
安全な Google Cloud ネットワークの構築
Earned 11月 23, 2020 EST
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 11月 23, 2020 EST
Google Cloud ネットワークの設定
Earned 11月 19, 2020 EST
Google Cloud におけるアプリ開発環境の設定
Earned 11月 16, 2020 EST
Cloud Development
Earned 11月 16, 2020 EST
DEPRECATED Application Development - Java
Earned 11月 16, 2020 EST
DEPRECATED Application Development - Python
Earned 11月 13, 2020 EST
ベースライン: データ、ML、AI
Earned 11月 11, 2020 EST
ベースライン: インフラストラクチャ
Earned 11月 6, 2020 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 11月 6, 2020 EST
DevOps の基礎
Earned 11月 4, 2020 EST
DEPRECATED Cloud Architecture
Earned 11月 4, 2020 EST
クラウド エンジニアリング
Earned 11月 3, 2020 EST
DEPRECATED BigQuery Basics for Data Analysts
Earned 11月 3, 2020 EST
Google Cloud での Kubernetes アプリケーションのデプロイ
Earned 11月 2, 2020 EST
Google Cloud の Kubernetes
Earned 10月 30, 2020 EDT
Compute Engine でのロード バランシングの実装
Earned 10月 29, 2020 EDT
Google Cloud Essentials
Earned 10月 29, 2020 EDT