ご自身に最適な Google Cloud トレーニングをお探しください。
Google Cloud では、学習者のことを念頭に置いて設計された、980 以上の学習アクティビティを含む包括的なカタログをご用意しています。さまざまなアクティビティ形式のコン テンツで構成されたカタログから、短時間の単独ラボのほか、一連の動画、ドキュメント、 ラボ、テストで構成されるマルチモジュール コースをお選びいただけます。ラボでは、 実際のクラウド リソースへのアクセスに必要な一時的な認証情報が付与されるため、 本番さながらの状況で Google Cloud について学習できます。修了した学習アクティビ ティのバッジを獲得したり、Google Cloud での成果を定義、記録、分析したりできます。
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コース おすすめ Feature Engineering
This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
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コース おすすめ Enterprise Database Migration
This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to Google Cloud while taking advantage …
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コース おすすめ Networking in Google Cloud: Routing and Addressing
Welcome to the second course in the networking and Google Cloud series routing and addressing. In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities. Module one will lay the foundation by exploring network routing and addressing in Googl…
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コース おすすめ Reliable Google Cloud Infrastructure: Design and Process
This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in eithe…
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コース おすすめ Machine Learning Operations (MLOps): Getting Started
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professiona…
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コース おすすめ Production Machine Learning Systems
This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed t…
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コース おすすめ API Design and Fundamentals of Google Cloud's Apigee API Platform
In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API life cycle, and how the Apigee API platform helps you manage all aspects of the life cycle. You learn about how APIs can be designed using API proxies, and how APIs are packaged as API prod…
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コース おすすめ Managing and Securing the Apigee Hybrid API Platform
This course discusses how environments are managed in Apigee hybrid, and how runtime plane components are secured. You will also learn how to deploy and debug API proxies in Apigee hybrid, and about capacity planning and scaling.
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コース おすすめ Computer Vision Fundamentals with Google Cloud
This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear mod…
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コース おすすめ Recommendation Systems on Google Cloud
In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.