On-demand activities
כשתכננו את Google Cloud, חשבנו עליכם. קטלוג ההדרכה שלנו מכיל למעלה מ-980 פעילויות שונות ממגוון סוגים. תוכלו לבחור מבין שיעורי Lab קצרים ואישיים או קורסים עם מודולים מרובים שמכילים סרטונים, מסמכים, שיעורי Lab ובחנים. בשיעורי ה-Lab תקבלו פרטי כניסה זמניים למשאבים עצמם בענן, כדי שתוכלו לתרגל במו ידיכם את השימוש ב-Google Cloud. תקבלו גם תגים על השיעורים והקורסים שתסיימו, ותוכלו לעקוב אחרי ההתקדמות ולהגדיר מה מבחינתכם נחשב להצלחה ב-Google Cloud!
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Lab Featured 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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Lab Featured 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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Lab Featured 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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Lab Featured 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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Lab Featured 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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Lab Featured Respond and recover from a data breach
Remediate a list of security issues based on a PCI compliance report
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Lab Featured 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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Lab Featured 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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Lab Featured 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.