AI-100 Exam Question 1

Your company plant to monitor twitter hashtags. and then to build a graph of connected people and places that contains the associated sentiment.
The monitored hashtags use several languages, but the graph will be displayed in English.
You need to recommend the required Azure Cognitive Services endpoints (or the planned graph Which Cognitive Services endpoints should you recommend?
  • AI-100 Exam Question 2

    You design an Al workflow that combines data from multiple data sources for analysis. The data sources are composed of:
    * JSON files uploaded to an Azure Storage account
    * On-premises Oracle databases
    * Azure SQL databases
    Which service should you use to ingest the data?
  • AI-100 Exam Question 3

    You are building an Azure Analysis Services cube for your Al deployment.
    The source data for the cube is located in an on premises network in a Microsoft SQL Server database.
    You need to ensure that the Azure Analysis Services service can access the source data.
    What should you deploy to your Azure subscription?
  • AI-100 Exam Question 4

    You have a Face API solution that updates in real time. A pilot of the solution runs successfully on a small dataset.
    When you attempt to use the solution on a larger dataset that continually changes, the performance degrades, slowing how long it takes to recognize existing faces.
    You need to recommend changes to reduce the time it takes to recognize existing faces without increasing costs.
    What should you recommend?
  • AI-100 Exam Question 5

    Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
    After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
    You have Azure IoT Edge devices that generate streaming data.
    On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.
    Solution: You deploy an Azure Machine Learning model as an IoT Edge module.
    Does this meet the goal?