On-Demand-Aktivitäten
Finden Sie die für Sie richtigen On-Demand-Lernaktivitäten. Labs sind kurze Lernaktivitäten, in denen Ihnen über einen direkten, temporären, praxisorientierten Zugriff auf echte Cloud-Ressourcen spezifische Inhalte vermittelt werden. Kurse sind längere Aktivitäten, die aus mehreren Modulen mit Videos, Dokumenten, praxisorientierten Labs und Quizaufgaben bestehen. Aufgabenreihen sind ähnlich, aber in der Regel kürzer und enthalten nur Labs.
1073 Ergebnisse
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Lab Tipp Export Data from Google Earth Engine to BigQuery
In this lab, you will learn how to export data from Google Earth Engine to BigQuery using the Earth Engine Code Editor.
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Lab Tipp Monitoring and Managing Bigtable Health and Performance
In this lab, you monitor disk and CPU usage in a Bigtable instance, update an existing cluster to apply node autoscaling, implement replication in an instance, and back up and restore data in Bigtable.
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Lab Tipp Exploring NCAA Data with BigQuery
Use BigQuery to explore the NCAA dataset of basketball games, teams, and players. The data covers plays from 2009 and scores from 1996. Watch How the NCAA is using Google Cloud to tap into decades of sports data.
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Lab Tipp Creating a Persistent Disk
In this hands-on lab, you will learn how to create a persistent disk and use it on a Google Compute Engine virtual machine. You will also learn about zones, regions, and different disk types. Watch the short preview Create a Persistent Disk, GCP Essentials.
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Lab Tipp Creating Date-Partitioned Tables in BigQuery
In this lab, you learn how to query and create partitioned tables to improve query performance and reduce resource usage.
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Lab Tipp Build a BI Dashboard Using Looker Studio and BigQuery
In this lab, you will learn how to build a BI dashboard with Looker Studio as the front end, powered by BigQuery on the back end.
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Lab Tipp Generative AI: ML Engineer Revision
Arcade chatbot lab to learn about the Professional ML Engineer
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Lab Tipp Summarize Text using SQL and LLMs in BigQuery ML
In this lab, you will explore how to perform summarization of source code from GitHub repos and identification of the language of programming in the repo, using Vertex AI Large Language Model (LLM) for text generation.