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The DP-100 exam is beneficial for data scientists and engineers who are looking for a career in the data science field. Designing and Implementing a Data Science Solution on Azure certification provides a competitive advantage to the candidates and opens up new job opportunities. Moreover, the DP-100 Certification helps the organizations to identify the skilled data scientists and engineers who can design and implement data science solutions on Azure.

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What is more difficult is not only passing the Microsoft DP-100 Certification Exam, but the acute anxiety and the excessive burden also make the candidate nervous to qualify for the Designing and Implementing a Data Science Solution on Azure certification. If you are going through the same tough challenge, do not worry because Microsoft is here to assist you.

The Microsoft DP-100 exam comprises of multiple-choice questions and performance-based tasks that measure the candidate's ability to implement data solutions, analyze data, and create machine learning models using Azure technologies. DP-100 Exam is designed to evaluate the candidate's skills in various areas such as data preprocessing, model selection, data visualization, and deployment.

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q165-Q170):

NEW QUESTION # 165
You need to evaluate the potential risk of exposing personal information based on the values of epsilon and delta for differential privacy. You create a privacy report.
What does an epsilon value greater than one represent?

A. The data used in the report is very noisy.
B. The privacy of data is preserved and there is limited impact on data accuracy.
C. There is a high risk of exposing the actual data that is uses to generate the report.

Answer: C

Explanation:
When epsilon is greater than one, it indicates that the privacy guarantee is weakened, and there is a higher risk of revealing sensitive or personal information from the data used in the report. A larger epsilon allows for more noise in the data, which can reduce privacy protection. Typically, smaller values of epsilon are preferred to provide stronger privacy guarantees.

NEW QUESTION # 166
You use Azure Machine Learning designer to create a real-time service endpoint. You have a single Azure Machine Learning service compute resource. You train the model and prepare the real-time pipeline for deployment You need to publish the inference pipeline as a web service. Which compute type should you use?

A. HDInsight
B. a new Machine Learning Compute resource
C. the existing Machine Learning Compute resource
D. Azure Kubernetes Services
E. Azure Databricks

Answer: D

Explanation:
Explanation
Azure Kubernetes Service (AKS) can be used real-time inference.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target

NEW QUESTION # 167
You need to select a feature extraction method.
Which method should you use?

A. Mood's median test
B. Mutual information
C. Kendall correlation
D. Permutation Feature Importance

Answer: C

Explanation:
Explanation
In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's tau coefficient (after the Greek letter ), is a statistic used to measure the ordinal association between two measured quantities.
It is a supported method of the Azure Machine Learning Feature selection.
Scenario: When you train a Linear Regression module using a property dataset that shows data for property prices for a large city, you need to determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. You must ensure that the distribution of the features across multiple training models is consistent.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/feature-selection-modules

NEW QUESTION # 168
You create a multi-class image classification deep learning model.
The model must be retrained monthly with the new image data fetched from a public web portal. You create an Azure Machine Learning pipeline to fetch new data, standardize the size of images, and retrain the model.
You need to use the Azure Machine Learning SDK to configure the schedule for the pipeline.
Which four 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:

Explanation:
Step 1: Publish the pipeline.
To schedule a pipeline, you'll need a reference to your workspace, the identifier of your published pipeline, and the name of the experiment in which you wish to create the schedule.
Step 2: Retrieve the pipeline ID.
Needed for the schedule.
Step 3: Create a ScheduleRecurrence..
To run a pipeline on a recurring basis, you'll create a schedule. A Schedule associates a pipeline, an experiment, and a trigger.
First create a schedule. Example: Create a Schedule that begins a run every 15 minutes:
recurrence = ScheduleRecurrence(frequency="Minute", interval=15)
Step 4: Define an Azure Machine Learning pipeline schedule..
Example, continued:
recurring_schedule = Schedule.create(ws, name="MyRecurringSchedule",
description="Based on time",
pipeline_id=pipeline_id,
experiment_name=experiment_name,
recurrence=recurrence)
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-schedule-pipelines

NEW QUESTION # 169
You create an Azure Machine Learning dataset. You use the Azure Machine Learning designer to transform the dataset by using an Execute Python Script component and custom code.
You must upload the script and associated libraries as a script bundle.
You need to configure the Execute Python Script component.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE Each correct selection is worth one point.

Answer:

Explanation:

Explanation

NEW QUESTION # 170
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