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Microsoft DP-100 (Designing and Implementing a Data Science Solution on Azure) Certification Exam is designed for professionals who want to validate their expertise in designing and implementing data science solutions using Microsoft Azure technologies. Designing and Implementing a Data Science Solution on Azure certification exam is aimed at data scientists, data engineers, and other professionals who work with data and want to demonstrate their skills in this field. DP-100 exam tests the candidate's knowledge of Azure data services, machine learning, and other related technologies.

Obtaining the DP-100 Certification demonstrates the candidate's proficiency in designing and implementing data science solutions on Azure. Designing and Implementing a Data Science Solution on Azure certification provides a competitive edge in the job market and opens up various career opportunities for the candidate. The DP-100 certification is also a prerequisite for other advanced Azure-based data science certifications, such as the DP-200 (Implementing an Azure Data Solution) and DP-201 (Designing an Azure Data Solution) certifications.

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q502-Q507):

NEW QUESTION # 502
You are using hyperparameter tuning in Azure Machine Learning Python SDK v2 to train a model. You configure the hyperparameter tuning experiment by running the following code:

For each of the following statements select Yes if the statement is true. Otherwise, select No. NOTE: Fach correct selection is worth one paint.

Answer:

Explanation:


NEW QUESTION # 503
You create an Azure Machine Learning workspace.
You must implement dedicated compute for model training in the workspace by using Azure Synapse compute resources. The solution must attach the dedicated compute and start an Azure Synapse session.
You need to implement the compute resources.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - Create a linked service by using Azure Machine Learning studio.
2 - Create an Azure Synapse workspace by using the Azure portal.
3 - Create an Apache Spark pool by using the Azure portal.


NEW QUESTION # 504
You need to implement a feature engineering strategy for the crowd sentiment local models.
What should you do?

Answer: A


NEW QUESTION # 505
You plan to explore demographic data for home ownership in various cities. The data is in a CSV file with the following format:
age,city,income,home_owner
21,Chicago,50000,0
35,Seattle,120000,1
23,Seattle,65000,0
45,Seattle,130000,1
18,Chicago,48000,0
You need to run an experiment in your Azure Machine Learning workspace to explore the data and log the results. The experiment must log the following information:
the number of observations in the dataset
a box plot of income by home_owner
a dictionary containing the city names and the average income for each city You need to use the appropriate logging methods of the experiment's run object to log the required information.
How should you complete the code? To answer, drag the appropriate code segments to the correct locations. Each code segment may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 506
Hotspot Question
You must use an Azure Data Science Virtual Machine (DSVM) as a compute target.
You need to attach an existing DSVM to the workspace by using the Azure Machine Learning SDK for Python.
How should you complete the following code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
https://learn.microsoft.com/en-us/python/api/azureml-
core/azureml.core.compute.remote.remotecompute?view=azure-ml-py


NEW QUESTION # 507
......

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