On-demand activities
Find the right on-demand learning activities for you. Labs are short learning activities that teach you a specific lesson by giving you direct, temporary, hands-on access to real cloud resources. Courses are longer activities, consisting of several modules made of videos, documents, hands-on labs and quizzes. Finally, quests are similar, but are usually shorter and contain only labs.
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Atelier Sélection APIs Explorer: Cloud SQL
In this lab, you will get hands-on practice with the Cloud SQL API and its associated methods by making calls through the APIs Explorer tool.
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Atelier Sélection Prepare Data for ML APIs on Google Cloud: Challenge Lab
This challenge lab tests your skills and knowledge from the labs in the Prepare Data for ML APIs on Google Cloud course. You should be familiar with the content of the labs before attempting this lab.
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Atelier Sélection Distributed Image Processing in Cloud Dataproc
In this lab, you will learn how to use Apache Spark on Cloud Dataproc to distribute a computationally intensive image processing task onto a cluster of machines.
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Atelier Sélection Setting up Generative Knowledge Assist in the Agent Assist console
This lab provides a step-by-step approach to creating a Data Store, adding documents to the Data Store, creating a GKA infobot agent and attaching the Data Store to it, setting up an Agent Assist conversation profile, and linking it to the GKA Agent for Knowledge Assist using the Agent Assist console.
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Atelier Sélection Configure Secure RDP using a Windows Bastion Host: Challenge Lab
This is a Challenge Lab where you must complete a series of tasks within a limited time period. You will be asked to deploy the secure Windows machine that is not configured for external communication inside a new VPC subnet, then deploy the Microsoft Internet Information Server on that secure machine.
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Atelier Sélection Respond and recover from a data breach
Remediate a list of security issues based on a PCI compliance report
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Atelier Sélection Create Text Embeddings for a Vector Store using LangChain
In this lab, you learn how to use LangChain to store documents as embeddings in a vector store. You will use the LangChain framework to split a set of documents into chunks, vectorize (embed) each chunk and then store the embeddings in a vector database.
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Atelier Sélection Explore false positives through incident detection
Aanalyze a false positive threat using the Security Command Center (SCC) and take action to address it.
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Atelier Sélection Introduction to Cloud Bigtable (Java)
Learn how to avoid common mistakes with schema design, import data in a sequence file, and query your data using Cloud Bigtable with the Java HBase client.