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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Data Science Solution on Azure |
| Exam Number: | DP-100 |
| Passing Score: | 700 |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 100 minutes |
| Certificate Validity Period: | 1 year |
| Available Languages: | French, Chinese (Traditional), Indonesian (Indonesia), Russian, English, Portuguese (Brazil), Japanese, German, Spanish, Italian, Arabic (Saudi Arabia), Chinese (Simplified), Korean |
| Exam Format: | Drag and drop, Yes/No, Case studies, Multiple choice, Multiple select |
| Exam Price: | $165 USD |
| Related Certifications: | Microsoft Certified: Azure AI Engineer Associate Microsoft Certified: Azure Data Engineer Associate |
| Recommended Training: | Microsoft Learn Learning Path Course DP-100T01-A: Designing and Implementing a Data Science Solution on Azure |
| Exam Registration: | Pearson VUE Scheduling Microsoft Learn Registration |
| Sample Questions: | Microsoft DP-100 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | No mandatory prerequisites; recommended knowledge: Azure fundamentals, Python programming, data science concepts, machine learning frameworks (Scikit-learn, PyTorch, Tensorflow) |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-100 |
The Microsoft DP-100 exam is one of the top-rated career advancement certifications in the market. With the Designing and Implementing a Data Science Solution on Azure DP-100 certification exam everyone can validate their skills and knowledge after passing the DP-100 exam. The Microsoft DP-100 certification exam will recognize your expertise and knowledge in the market. You will get solid proof of your proven skill set. There are other countless benefits that you can gain after passing the Designing and Implementing a Data Science Solution on Azure DP-100 Certification Exam. But the problem is how to pass the Microsoft DP-100 exam. The Microsoft DP-100 certification exam is not an easy exam. It is a challenging exam that gives taught time to candidates. However, with the assistance of Microsoft DP-100 PDF Questions and practice tests you can pass the DP-100 exam easily.
Candidates with permission to take DP-100 Exam are those aspiring to become Azure data scientists and have formed huge knowledge in both data science and machine learning workloads based on Azure.
NEW QUESTION # 54
You manage an Azure Machine Learning workspace. The development environment for managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks.
A Synapse Spark Compute is currently attached and uses system-assigned identity.
You need to use Python code to update the Synapse Spark Compute to use a user-assigned identity.
Solution: Pass the UserAssignedldentity class object to the SynapseSparkCompute class.
Does the solution meet the goat?
Answer: A
NEW QUESTION # 55
You plan to use Hyperdrive to optimize the hyperparameters selected when training a model. You create the following code to define options for the hyperparameter experiment
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.hyperdrive.hyperdriveconfig
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
NEW QUESTION # 56
You create an Azure Machine Learning workspace.
You must create a custom role named DataScientist that meets the following requirements:
* Role members must not be able to delete the workspace.
* Role members must not be able to create, update, or delete compute resource in the workspace.
* Role members must not be able to add new users to the workspace.
You need to create a JSON file for the DataScientist role in the Azure Machine Learning workspace.
The custom role must enforce the restrictions specified by the IT Operations team.
Which JSON code segment should you use?
Answer: C
Explanation:
The following custom role can do everything in the workspace except for the following actions:
* It can't create or update a compute resource.
* It can't delete a compute resource.
* It can't add, delete, or alter role assignments.
* It can't delete the workspace.
To create a custom role, first construct a role definition JSON file that specifies the permission and scope for the role. The following example defines a custom role named "Data Scientist Custom" scoped at a specific workspace level:
data_scientist_custom_role.json :
{
"Name": "Data Scientist Custom",
"IsCustom": true,
"Description": "Can run experiment but can't create or delete compute.",
"Actions": ["*"],
"NotActions": [
"Microsoft.MachineLearningServices/workspaces/*/delete",
"Microsoft.MachineLearningServices/workspaces/write",
"Microsoft.MachineLearningServices/workspaces/computes/*/write",
"Microsoft.MachineLearningServices/workspaces/computes/*/delete",
"Microsoft.Authorization/*/write"
],
"AssignableScopes": [
"/subscriptions/<subscription_id>/resourceGroups/<resource_group_name>/providers/Microsoft.MachineLearni
]
}
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-assign-roles
NEW QUESTION # 57
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 in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are a data scientist using Azure Machine Learning Studio.
You need to normalize values to produce an output column into bins to predict a target column.
Solution: Apply a Quantiles normalization with a QuantileIndex normalization.
Does the solution meet the GOAL?
Answer: A
Explanation:
Use the Entropy MDL binning mode which has a target column.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/group-data-into-bins
NEW QUESTION # 58
You use an Azure Machine Learning workspace. Azure Data Factor/ pipeline, and a dataset monitor that runs en a schedule to detect data drift.
You need to Implement an automated workflow to trigger when the dataset monitor detects data drift and launch the Azure Data Factory pipeline to update the dataset. The solution must minimize the effort to configure the workflow.
How should you configure the workflow? To answer select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 59
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