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Microsoft DP-100 Designing and Implementing a Data Science Solution on Azure Exam Practice Test

Demo: 62 questions
Total 476 questions

Designing and Implementing a Data Science Solution on Azure Questions and Answers

Question 1

You need to replace the missing data in the AccessibilityToHighway columns.

How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 2

You need to set up the Permutation Feature Importance module according to the model training requirements.

Which properties should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 3

You need to identify the methods for dividing the data according to the testing requirements.

Which properties should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 4

You need to select a feature extraction method.

Which method should you use?

Options:

A.

Spearman correlation

B.

Mutual information

C.

Mann-Whitney test

D.

Pearson’s correlation

Question 5

You need to select a feature extraction method.

Which method should you use?

Options:

A.

Mutual information

B.

Mood’s median test

C.

Kendall correlation

D.

Permutation Feature Importance

Question 6

You need to visually identify whether outliers exist in the Age column and quantify the outliers before the outliers are removed.

Which three Azure Machine Learning Studio modules should you use in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Options:

Question 7

You need to configure the Feature Based Feature Selection module based on the experiment requirements and datasets.

How should you configure the module properties? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 8

You need to implement early stopping criteria as suited in the model training requirements.

Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Options:

Question 9

You need to configure the Edit Metadata module so that the structure of the datasets match.

Which configuration options should you select? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 10

You need to identify the methods for dividing the data according, to the testing requirements.

Which properties should you select? To answer, select the appropriate option-, m the answer area. NOTE: Each correct selection is worth one point.

Options:

Question 11

You need to correct the model fit issue.

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.

Options:

Question 12

You need to configure the Permutation Feature Importance module for the model training requirements.

What should you do? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 13

You need to produce a visualization for the diagnostic test evaluation according to the data visualization requirements.

Which three modules should you recommend be used in sequence? To answer, move the appropriate modules from the list of modules to the answer area and arrange them in the correct order.

Options:

Question 14

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.

Options:

Question 15

You have a dataset that contains 2,000 rows. You are building a machine learning classification model by using Azure Learning Studio. You add a Partition and Sample module to the experiment.

You need to configure the module. You must meet the following requirements:

Divide the data into subsets

Assign the rows into folds using a round-robin method

Allow rows in the dataset to be reused

How should you configure the module? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 16

You manage an Azure Machine Learning workspace named workspace 1 with a compute instance named computet.

You must remove a kernel named kernel 1 from computet1. You connect to compute 1 by using noa terminal window from workspace 1.

You need to enter a command in the terminal window to remove kernel 1.

Which command should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection it worth one point.

Options:

Question 17

You have a feature set containing the following numerical features: X, Y, and Z.

The Poisson correlation coefficient (r-value) of X, Y, and Z features is shown in the following image:

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

Options:

Question 18

You use the Azure Machine learning SDK v2 tor Python and notebooks to tram a model. You use Python code to create a compute target, an environment, and a taring script. You need to prepare information to submit a training job.

Which class should you use?

Options:

A.

MLClient

B.

command

C.

BuildContext

D.

EndpointConnection

Question 19

You have an Azure Machine Learning workspace that contains a training cluster and an inference cluster.

You plan to create a classification model by using the Azure Machine Learning designer.

You need to ensure that client applications can submit data as HTTP requests and receive predictions as responses.

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.

Options:

Question 20

You create an Azure Databricks workspace and a linked Azure Machine Learning workspace.

You have the following Python code segment in the Azure Machine Learning workspace:

import mlflow

import mlflow.azureml

import azureml.mlflow

import azureml.core

from azureml.core import Workspace

subscription_id = 'subscription_id'

resourse_group = 'resource_group_name'

workspace_name = 'workspace_name'

ws = Workspace.get(name=workspace_name,

subscription_id=subscription_id,

resource_group=resource_group)

experimentName = "/Users/{user_name}/{experiment_folder}/{experiment_name}"

mlflow.set_experiment(experimentName)

uri = ws.get_mlflow_tracking_uri()

mlflow.set_tracking_uri(uri)

Instructions: For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Options:

Question 21

You create an Azure Machine Learning compute target named ComputeOne by using the STANDARD_D1 virtual machine image.

You define a Python variable named was that references the Azure Machine Learning workspace. You run the following Python code:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Options:

Question 22

You have an Azure Machine Learning workspace. You are running an experiment on your local computer.

You need to use MLflow Tracking to store metrics and artifacts from your local experiment runs in the workspace.

In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

Options:

Question 23

You create a new Azure subscription. No resources are provisioned in the subscription.

You need to create an Azure Machine Learning workspace.

What are three possible ways to achieve this goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

A.

Run Python code that uses the Azure ML SDK library and calls the Workspace.create method with name, subscription_id, resource_group, and location parameters.

B.

Use an Azure Resource Management template that includes a Microsoft.MachineLearningServices/workspaces resource and its dependencies.

C.

Use the Azure Command Line Interface (CLI) with the Azure Machine Learning extension to call the azgroup create function with --name and --location parameters, and then the az ml workspace createfunction, specifying –w and –g parameters for the workspace name and resource group.

D.

Navigate to Azure Machine Learning studio and create a workspace.

E.

Run Python code that uses the Azure ML SDK library and calls the Workspace.get method with name,subscription_id, and resource_group parameters.

Question 24

You have a Jupyter Notebook that contains Python code that is used to train a model.

You must create a Python script for the production deployment. The solution must minimize code maintenance.

Which two actions should you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

Options:

A.

Refactor the Jupyter Notebook code into functions

B.

Save each function to a separate Python file

C.

Define a main() function in the Python script

D.

Remove all comments and functions from the Python script

Question 25

You are producing a multiple linear regression model in Azure Machine Learning Studio.

Several independent variables are highly correlated.

You need to select appropriate methods for conducting effective feature engineering on all the data.

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.

Options:

Question 26

You have an Azure Machine Learning workspace that contains a CPU-based compute cluster and an Azure Kubernetes Services (AKS) inference cluster. You create a tabular dataset containing data that you plan to use to create a classification model.

You need to use the Azure Machine Learning designer to create a web service through which client applications can consume the classification model by submitting new data and getting an immediate prediction as a response.

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.

Options:

Question 27

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 have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder.

You must run the script as an Azure ML experiment on a compute cluster named aml-compute.

You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster.

Solution: Run the following code:

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 28

You plan to run a Python script as an Azure Machine Learning experiment.

The script must read files from a hierarchy of folders. The files will be passed to the script as a dataset argument.

You must specify an appropriate mode for the dataset argument.

Which two modes can you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

A.

to_pandas_dataframe ()

B.

as_download()

C.

as_upload()

D.

as mount ()

Question 29

You have an Azure Machine Learning workspace.

You run the following code in a Python environment in which the configuration file for your workspace has been downloaded.

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

Options:

Question 30

You are performing a classification task in Azure Machine Learning Studio.

You must prepare balanced testing and training samples based on a provided data set.

You need to split the data with a 0.75:0.25 ratio.

Which value should you use for each parameter? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 31

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 an Equal Width with Custom Start and Stop binning mode.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 32

You are using a decision tree algorithm. You have trained a model that generalizes well at a tree depth equal to 10.

You need to select the bias and variance properties of the model with varying tree depth values.

Which properties should you select for each tree depth? To answer, select the appropriate options in the answer area.

Options:

Question 33

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 have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.

You plan to add a new Jupyter kernel that will be accessible from the same terminal session.

You need to perform the task that must be completed before you can add the new kernel.

Solution: Delete the Python 3.8 - AzureML kernel.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 34

A set of CSV files contains sales records. All the CSV files have the same data schema.

Each CSV file contains the sales record for a particular month and has the filename sales.csv. Each file in stored in a folder that indicates the month and year when the data was recorded. The folders are in an Azure blob container for which a datastore has been defined in an Azure Machine Learning workspace. The folders are organized in a parent folder named sales to create the following hierarchical structure:

At the end of each month, a new folder with that month’s sales file is added to the sales folder.

You plan to use the sales data to train a machine learning model based on the following requirements:

You must define a dataset that loads all of the sales data to date into a structure that can be easily converted to a dataframe.

You must be able to create experiments that use only data that was created before a specific previous month, ignoring any data that was added after that month.

You must register the minimum number of datasets possible.

You need to register the sales data as a dataset in Azure Machine Learning service workspace.

What should you do?

Options:

A.

Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file every month. Register the dataset with the name sales_dataset each month, replacing theexisting dataset and specifying a tag named month indicating the month and year it was registered. Usethis dataset for all experiments.

B.

Create a tabular dataset that references the datastore and specifies the path 'sales/*/sales.csv', register the dataset with the name sales_dataset and a tag named month indicating the month and year it was registered, and use this dataset for all experiments.

C.

Create a new tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/ sales.csv' file every month. Register the dataset with the name sales_dataset_MM-YYYY each month with appropriate MM and YYYY values for the month and year. Use the appropriate month-specific dataset for experiments.

D.

Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/sales.csv' file. Register the dataset with the name sales_dataset each month as a new version and with a tag named month indicating the month and year it was registered. Use this dataset for all experiments,identifying the version to be used based on the month tag as necessary.

Question 35

You manage an Azure Machine Learning workspace.

You must define the execution environments for your jobs and encapsulate the dependencies for your code.

You need to configure the environment from a Docker build context.

How should you complete the rode segment? To answer, select the appropriate option in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 36

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 have a Python script named train.py in a local folder named scripts. The script trains a regression model by using scikit-learn. The script includes code to load a training data file which is also located in the scripts folder.

You must run the script as an Azure ML experiment on a compute cluster named aml-compute.

You need to configure the run to ensure that the environment includes the required packages for model training. You have instantiated a variable named aml-compute that references the target compute cluster.

Solution: Run the following code:

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 37

You train a model and register it in your Azure Machine Learning workspace. You are ready to deploy the model as a real-time web service.

You deploy the model to an Azure Kubernetes Service (AKS) inference cluster, but the deployment fails because an error occurs when the service runs the entry script that is associated with the model deployment.

You need to debug the error by iteratively modifying the code and reloading the service, without requiring a re-deployment of the service for each code update.

What should you do?

Options:

A.

Register a new version of the model and update the entry script to load the new version of the model from its registered path.

B.

Modify the AKS service deployment configuration to enable application insights and re-deploy to AKS.

C.

Create an Azure Container Instances (ACI) web service deployment configuration and deploy the model on ACI.

D.

Add a breakpoint to the first line of the entry script and redeploy the service to AKS.

E.

Create a local web service deployment configuration and deploy the model to a local Docker container.

Question 38

You create an Azure Machine Learning workspace.

You plan to write an Azure Machine Learning SDK for Python v2 script that logs an image for an experiment. The logged image must be available from the images tab in Azure Machine Learning Studio.

You need to complete the script.

Which code segments should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 39

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.

Options:

Question 40

You are a data scientist creating a linear regression model.

You need to determine how closely the data fits the regression line.

Which metric should you review?

Options:

A.

Coefficient of determination

B.

Recall

C.

Precision

D.

Mean absolute error

E.

Root Mean Square Error

Question 41

You manage an Azure Machine Learning workspace That has an Azure Machine Learning datastore.

Data must be loaded from the following sources:

• a credential-less Azure Blob Storage

• an Azure Data Lake Storage (ADLS) Gen 2 which is not a credential-less datastore

You need to define the authentication mechanisms to access data in the Azure Machine Learning datastore.

Which data access mechanism should you use? To answer, move the appropriate data access mechanisms to the correct storage types. You may use each data access mechanism once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

Options:

Question 42

You create a multi-class image classification deep learning model.

You train the model by using PyTorch version 1.2.

You need to ensure that the correct version of PyTorch can be identified for the inferencing environment when the model is deployed.

What should you do?

Options:

A.

Save the model locally as a.pt file, and deploy the model as a local web service.

B.

Deploy the model on computer that is configured to use the default Azure Machine Learning condaenvironment.

C.

Register the model with a .pt file extension and the default version property.

D.

Register the model, specifying the model_framework and model_framework_version properties.

Question 43

You run a script as an experiment in Azure Machine Learning.

You have a Run object named run that references the experiment run. You must review the log files that were generated during the experiment run.

You need to download the log files to a local folder for review.

Which two code segments can you run to achieve this goal? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

A.

run.get_details()

B.

run.get_file_names()

C.

run.get_metrics()

D.

run.download_files(output_directory='./runfiles')

E.

run.get_all_logs(destination='./runlogs')

Question 44

You have an Azure Machine Learning workspace. You plan to tune model hyperparameters by using a sweep job.

You need to find a sampling method that supports early termination of low-performance jobs and continuous hyperpara meters.

Solution: Use the Bayesian sampling method over the hyperparameter space.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 45

You are creating a classification model for a banking company to identify possible instances of credit card fraud. You plan to create the model in Azure Machine Learning by using automated machine learning.

The training dataset that you are using is highly unbalanced.

You need to evaluate the classification model.

Which primary metric should you use?

Options:

A.

normalized_mean_absolute_error

B.

[spearman_correlation

C.

AUC.weighted

D.

accuracy

E.

normalized_root_mean_squared_error

Question 46

You create an Azure Machine Learning workspace.

You must use the Python SDK v2 to implement an experiment from a Jupiter notebook in the workspace. The experiment must log string metrics.

You need to implement the method to log the string metrics.

Which method should you use?

Options:

A.

mlflow.log-metric0

B.

mlflow.log. artifact0

C.

mlflow.log. dist0

D.

mlflow.log-text0

Question 47

You use the Azure Machine Learning service to create a tabular dataset named training.data. You plan to use this dataset in a training script.

You create a variable that references the dataset using the following code:

training_ds = workspace.datasets.get("training_data")

You define an estimator to run the script.

You need to set the correct property of the estimator to ensure that your script can access the training.data dataset

Which property should you set?

A)

B)

C)

D)

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 48

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 train and register a machine learning model.

You plan to deploy the model as a real-time web service. Applications must use key-based authentication to use the model.

You need to deploy the web service.

Solution:

Create an AksWebservice instance.

Set the value of the auth_enabled property to True.

Deploy the model to the service.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 49

You need to define a process for penalty event detection.

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.

Options:

Question 50

You need to use the Python language to build a sampling strategy for the global penalty detection models.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 51

You need to implement a feature engineering strategy for the crowd sentiment local models.

What should you do?

Options:

A.

Apply an analysis of variance (ANOVA).

B.

Apply a Pearson correlation coefficient.

C.

Apply a Spearman correlation coefficient.

D.

Apply a linear discriminant analysis.

Question 52

You need to build a feature extraction strategy for the local models.

How should you complete the code segment? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 53

You need to implement a scaling strategy for the local penalty detection data.

Which normalization type should you use?

Options:

A.

Streaming

B.

Weight

C.

Batch

D.

Cosine

Question 54

You need to define an evaluation strategy for the crowd sentiment models.

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.

Options:

Question 55

You need to define a process for penalty event detection.

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.

Options:

Question 56

You need to define a modeling strategy for ad response.

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.

Options:

Question 57

You need to modify the inputs for the global penalty event model to address the bias and variance issue.

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.

Options:

Question 58

You need to define an evaluation strategy for the crowd sentiment models.

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.

Options:

Question 59

You need to resolve the local machine learning pipeline performance issue. What should you do?

Options:

A.

Increase Graphic Processing Units (GPUs).

B.

Increase the learning rate.

C.

Increase the training iterations,

D.

Increase Central Processing Units (CPUs).

Question 60

You need to implement a new cost factor scenario for the ad response models as illustrated in the

performance curve exhibit.

Which technique should you use?

Options:

A.

Set the threshold to 0.5 and retrain if weighted Kappa deviates +/- 5% from 0.45.

B.

Set the threshold to 0.05 and retrain if weighted Kappa deviates +/- 5% from 0.5.

C.

Set the threshold to 0.2 and retrain if weighted Kappa deviates +/- 5% from 0.6.

D.

Set the threshold to 0.75 and retrain if weighted Kappa deviates +/- 5% from 0.15.

Question 61

You need to implement a model development strategy to determine a user’s tendency to respond to an ad.

Which technique should you use?

Options:

A.

Use a Relative Expression Split module to partition the data based on centroid distance.

B.

Use a Relative Expression Split module to partition the data based on distance travelled to the event.

C.

Use a Split Rows module to partition the data based on distance travelled to the event.

D.

Use a Split Rows module to partition the data based on centroid distance.

Question 62

You need to select an environment that will meet the business and data requirements.

Which environment should you use?

Options:

A.

Azure HDInsight with Spark MLlib

B.

Azure Cognitive Services

C.

Azure Machine Learning Studio

D.

Microsoft Machine Learning Server

Demo: 62 questions
Total 476 questions