On-demand activities
У Google Cloud ми створили для вас комплексний каталог, що містить понад 980 навчальних матеріалів. У ньому ви можете вибирати різні формати навчання. Це можуть бути невеликі індивідуальні практичні роботи чи багатомодульні курси з відео, документами, практичними завданнями й тестами. Для виконання практичних робіт ми надаємо вам тимчасові облікові дані для доступу до справжніх ресурсів у хмарі, тож ви можете вивчати Google Cloud у реальному середовищі. Отримуйте значки за виконані завдання, ставте собі цілі, відстежуйте й вимірюйте свої успіхи з Google Cloud.
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Курс Пропонується Creating New BigQuery Datasets and Visualizing Insights
This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sourc…
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Курс Пропонується Building No-Code Apps with AppSheet: Implementation
This course teaches you how to implement various capabilities that include data organization and management, application security, actions and integrations in your app using AppSheet. The course also includes topics on managing and upgrading your app, improving performance and troubleshooting issues with your app.
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Курс Пропонується Planning for a Google Workspace Deployment
Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series. In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on …
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Курс Пропонується Digital Transformation with Google Cloud
There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, …
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Курс Пропонується 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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Курс Пропонується 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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Курс Пропонується 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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Курс Пропонується 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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Курс Пропонується 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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Курс Пропонується 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…