Microsoft Data Certification DP-100 Certification Questions 2023 To Ensure Success

Jonnie Karnath2023-05-06T22:16:34+00:00

Want to get success in your Designing and Implementing a Data Science Solution on Azure exam? By using Microsoft Data Certification DP-100 certification questions, you increase your chances of passing the exam on your first attempt. They provide valuable insights into the exam format, the types of questions you can expect to encounter, and the key concepts you need to know to succeed. The significant benefit of Microsoft DP-100 certification questions is their ability to help you achieve brilliant exam results. They provide you with the knowledge and skills necessary to perform at your best, giving you the confidence you need to ace the exam.

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1. You define a datastore named ml-data for an Azure Storage blob container. In the container, you have a folder named train that contains a file named data.csv. You plan to use the file to train a model by using the Azure Machine Learning SDK.

You plan to train the model by using the Azure Machine Learning SDK to run an experiment on local compute.

You define a DataReference object by running the following code:

You need to load the training data.

Which code segment should you use?

A)

Option A

Option B

Option C

Option D

Option E

2. HOTSPOT

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.

3. You manage an Azure Machine Learning workspace by using the Azure CLI ml extension v2. You need to define a YAML schema to create a compute cluster.

Which schema should you use?

https://azuremlschemas.azureedge.net/latest/computdnstarKeichema.json

https://azuremlschemas.azureedge.net/latest/amlCompute.schemajson

https://azuremlschemas.azureedge.net/latest/vmCompute.schema.json

https://azuremlschemas.azureedge.net/latest/kubernetesCompute.schema.json

4. HOTSPOT

You are performing feature scaling by using the scikit-learn Python library for x.1 x2, and x3 features.

Original and scaled data 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.

5. You register a model that you plan to use in a batch inference pipeline.

The batch inference pipeline must use a ParallelRunStep step to process files in a file dataset. The script has the ParallelRunStep step runs must process six input files each time the inferencing function is called.

You need to configure the pipeline.

Which configuration setting should you specify in the ParallelRunConfig object for the PrallelRunStep step?

process_count_per_node= "6"

node_count= "6"

mini_batch_size= "6"

error_threshold= "6"

6. HOTSPOT

You manage an Azure Machine Learning workspace. You create an experiment named experiment1 by using the Azure Machine Learning Python SDK v2 and MLflow.

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

7. DRAG DROP

You create an Azure Machine Learning workspace.

You need to use the shared file system of the workspace to store a clone of a private Git repository.

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.

8. You use the following code to run a script as an experiment in Azure Machine Learning:

You must identify the output files that are generated by the experiment run.

You need to add code to retrieve the output file names.

Which code segment should you add to the script?

files = run.get_properties()

files= run.get_file_names()

files = run.get_details_with_logs()

files = run.get_metrics()

files = run.get_details()

9. HOTSPOT

You create a new Azure Databricks workspace.

You configure a new cluster for long-running tasks with mixed loads on the compute cluster as shown in the image below.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic. NOTE: Each correct selection is worth one point.

10. HOTSPOT

You create a script for training a machine learning model in Azure Machine Learning service.

You create an estimator by running the following 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.

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11. DRAG DROP

You are analyzing a raw dataset that requires cleaning.

You must perform transformations and manipulations by using Azure Machine Learning Studio.

You need to identify the correct modules to perform the transformations.

Which modules should you choose? To answer, drag the appropriate modules to the correct scenarios. Each module 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.

12. HOTSPOT

You plan to implement an Azure Machine Learning solution.

You have the following requirements:

• Run a Jupyter notebook to interactively tram a machine learning model.

• Deploy assets and workflows for machine learning proof of concept by using scripting rather than custom programming.

You need to select a development technique for each requirement

Which development technique should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

13. You use Azure Machine Learning to train a model based on a dataset named dataset1.

You define a dataset monitor and create a dataset named dataset2 that contains new data.

You need to compare dataset1 and dataset2 by using the Azure Machine Learning SDK for Python.

Which method of the DataDriftDetector class should you use?

run

get

backfill

update

14. HOTSPOT

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.

15. You are solving a classification task.

You must evaluate your model on a limited data sample by using k-fold cross validation. You start by

configuring a k parameter as the number of splits.

You need to configure the k parameter for the cross-validation.

Which value should you use?

k=0.5

k=0

k=5

k=1

16. DRAG DROP

You configure a Deep Learning Virtual Machine for Windows.

You need to recommend tools and frameworks to perform the following:

✑ Build deep neural network (DNN) models

✑ Perform interactive data exploration and visualization

Which tools and frameworks should you recommend? To answer, drag the appropriate tools to the correct tasks. Each tool 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.

17. You are building a machine learning model for translating English language textual content into French language textual content.

You need to build and train the machine learning model to learn the sequence of the textual content.

Which type of neural network should you use?

Multilayer Perceptions (MLPs)

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Generative Adversarial Networks (GANs)

18. You have a dataset that contains records of patients tested for diabetes. The dataset includes the patient s age.

You plan to create an analysis that will report the mean age value from the differentially private data derived from the dataset.

You need to identify the epsilon value to use in the analysis that minimizes the risk of exposing the actual data.

Which epsilon value should you use?

-1.5

-0.5

0.5

1.5

19. HOTSPOT

You have a dataset created for multiclass classification tasks that contains a normalized numerical feature set with 10,000 data points and 150 features.

You use 75 percent of the data points for training and 25 percent for testing. You are using the scikit-learn machine learning library in Python. You use X to denote the feature set and Y to denote class labels.

You create the following Python data frames:

You need to apply the Principal Component Analysis (PCA) method to reduce the dimensionality of the feature set to 10 features in both training and testing sets.

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.

20. DRAG DROP

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.

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21. You are developing a data science workspace that uses an Azure Machine Learning service.

You need to select a compute target to deploy the workspace.

What should you use?

Azure Data Lake Analytics

Azure Databrick .

Apache Spark for HDInsight.

Azure Container Service

22. 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.

to_pandas_dataframe ()

as_download()

as_upload()

as mount ()

23. You create an Azure Machine Learning workspace. You use the Azure Machine Learning SDK for Python.

You must create a dataset from remote paths. The dataset must be reusable within the workspace.

You need to create the dataset.

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.

24. HOTSPOT

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.

25. HOTSPOT

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.

26. DRAG DROP

You manage an Azure Machine Learning workspace named workspace1 and a Data Science Virtual Machine (DSVM) named DSMV1.

You must an experiment in DSMV1 by using a Jupiter notebook and Python SDK v2 code. You must store metrics and artifacts in workspace 1 You start by creating Python SCK v2 code to import ail required packages.

You need to implement the Python SOK v2 code to store metrics and article in workspace1.

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 the correctly order.

27. You create a batch inference pipeline by using the Azure ML SDK.

You configure the pipeline parameters by executing the following code:

You need to obtain the output from the pipeline execution.

Where will you find the output?

the Activity Log in the Azure portal for the Machine Learning workspace

a file named parallel_run_step.txt located in the output folder

the digitjdentification.py script

the Inference Clusters tab in Machine Learning studio

the debug log

28. You have an Azure Machine Learning (ML) model deployed to an online endpoint.

You need to review container logs from the endpoint by using Azure Ml Python SDK v2. The logs must include the console log from the inference server with print/log statements from the models scoring script.

What should you do first?

Create an instance of the the MLCIient class.

Create an instance of the OnlineDeploymentOperations class.

Connect by using SSH to the inference server.

Connect by using Docker tools to the inference server.

29. HOTSPOT

You load data from a notebook in an Azure Machine Learning workspace into a pandas dataframe named df. The data contains 10.000 patient records. Each record includes the Age property for the corresponding patient.

You must identify the mean age value from the differentially private data generated by SmartNoise SDK.

You need to complete the Python code that will generate the mean age value from the differentially private data.

Which code segments should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

30. HOTSPOT

You are retrieving data from a large datastore by using Azure Machine Learning Studio.

You must create a subset of the data for testing purposes using a random sampling seed based on the system clock.

You add the Partition and Sample module to your experiment.

You need to select the properties for the module.

Which values should you select? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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31. HOTSPOT

You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).

The remaining 1,000 rows represent class 1 (10 percent).

The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.

You need to configure the module.

Which values should you use? To answer, select the appropriate options in the dialog box in the answer area. NOTE: Each correct selection is worth one point.

32. You are creating a new experiment in Azure Machine Learning Studio. You have a small dataset that has missing values in many columns. The data does not require the application of predictors for each column. You plan to use the Clean Missing Data module to handle the missing data.

You need to select a data cleaning method.

Which method should you use?

Synthetic Minority Oversampling Technique (SMOTE)

Replace using MICE

Replace using; Probabilistic PCA

Normalization

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 plan to use a Python script to run an Azure Machine Learning experiment. The script creates a reference to the experiment run context, loads data from a file, identifies the set of unique values for the label column, and completes the experiment run:

from azureml.core import Run

import pandas as pd

run = Run.get_context()

data = pd.read_csv('data.csv')

label_vals = data['label'].unique()

# Add code to record metrics here run.complete()

The experiment must record the unique labels in the data as metrics for the run that can be reviewed later.

You must add code to the script to record the unique label values as run metrics at the point indicated by the comment.

Solution: Replace the comment with the following code:

run.log_table('Label Values', label_vals)

Does the solution meet the goal?

Yes

34. DRAG DROP

An organization uses Azure Machine Learning service and wants to expand their use of machine learning.

You have the following compute environments.

The organization does not want to create another compute environment.

You need to determine which compute environment to use for the following scenarios.

Which compute types should you use? To answer, drag the appropriate compute environments to the correct scenarios. Each compute environment 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.

35. 2.1.0

You run the following code:

You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:

Solution: Run the following code:

Does the solution meet the goal?

Yes

36. HOTSPOT

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.

37. 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 analyzing a numerical dataset which contain missing values in several columns.

You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.

You need to analyze a full dataset to include all values.

Solution: Use the last Observation Carried Forward (IOCF) method to impute the missing data points.

Does the solution meet the goal?

Yes

38. HOTSPOT

A biomedical research company plans to enroll people in an experimental medical treatment trial.

You create and train a binary classification model to support selection and admission of patients to the trial. The model includes the following features: Age, Gender, and Ethnicity.

The model returns different performance metrics for people from different ethnic groups.

You need to use Fairlearn to mitigate and minimize disparities for each category in the Ethnicity feature.

Which technique and constraint should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

39. You create a script that trains a convolutional neural network model over multiple epochs and logs the validation loss after each epoch. The script includes arguments for batch size and learning rate.

You identify a set of batch size and learning rate values that you want to try.

You need to use Azure Machine Learning to find the combination of batch size and learning rate that results in the model with the lowest validation loss.

What should you do?

Run the script in an experiment based on an AutoMLConfig object

Create a PythonScriptStep object for the script and run it in a pipeline

Use the Automated Machine Learning interface in Azure Machine Learning studio

Run the script in an experiment based on a ScriptRunConfig object

Run the script in an experiment based on a HyperDriveConfig object

40. You are a data scientist working for a bank and have used Azure ML to train and register a machine learning model that predicts whether a customer is likely to repay a loan.

You want to understand how your model is making selections and must be sure that the model does not violate government regulations such as denying loans based on where an applicant lives.

You need to determine the extent to which each feature in the customer data is influencing predictions.

What should you do?

Enable data drift monitoring for the model and its training dataset.

Score the model against some test data with known label values and use the results to calculate a confusion matrix.

Use the Hyperdrive library to test the model with multiple hyperparameter values.

Use the interpretability package to generate an explainer for the model.

Add tags to the model registration indicating the names of the features in the training dataset.

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41. You have an Azure Machine Learning workspace. You are connecting an Azure Data Lake Storage Gen2 account to the workspace as a data store. You need to authorize access from the workspace to the Azure Data Lake Storage Gen2 account.

What should you use?

Managed identity

SAS token

Service principal

Account key

42. You use Azure Machine Learning Studio to build a machine learning experiment.

You need to divide data into two distinct datasets.

Which module should you use?

Split Data

Load Trained Model

Assign Data to Clusters

Group Data into Bins

43. DRAG DROP

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.

44. HOTSPOT

You write code to retrieve an experiment that is run from your Azure Machine Learning workspace.

The run used the model interpretation support in Azure Machine Learning to generate and upload a model explanation.

Business managers in your organization want to see the importance of the features in the model.

You need to print out the model features and their relative importance in an output that looks similar to the following.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

45. HOTSPOT

You use Azure Machine Learning to train and register a model.

You must deploy the model into production as a real-time web service to an inference cluster named service-compute that the IT department has created in the Azure Machine Learning workspace.

Client applications consuming the deployed web service must be authenticated based on their Azure Active Directory service principal.

You need to write a script that uses the Azure Machine Learning SDK to deploy the model. The necessary modules have been imported.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

46. HOTSPOT

A coworker registers a datastore in a Machine Learning services workspace by using the following code:

You need to write code to access the datastore from a notebook.

47. You are using Azure Machine Learning to monitor a trained and deployed model. You implement Event Grid to respond to Azure Machine Learning events.

Model performance has degraded due to model input data changes.

You need to trigger a remediation ML pipeline based on an Azure Machine Learning event.

Which event should you use?

RunStatusChanged

DatasetDriftDetected

ModelDeployed

RunCompleted

48. HOTSPOT

You are analyzing the asymmetry in a statistical distribution.

The following image contains two density curves that show the probability distribution of two datasets.

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.

49. HOTSPOT

space and set up a development environment. You plan to train a deep neural network (DNN) by using the Tensorflow framework and by using estimators to submit training scripts.

You must optimize computation speed for training runs.

You need to choose the appropriate estimator to use as well as the appropriate training compute target configuration.

Which values should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

50. HOTSPOT

You have an Azure Machine learning workspace. The workspace contains a dataset with data in a tabular form.

You plan to use the Azure Machine Learning SDK for Python vl to create a control script that will load the dataset into a pandas dataframe in preparation for model training The script will accept a parameter designating the dataset

You need to complete the script.

How should you complete the script? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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51. 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 using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model.

You configure a HyperDriveConfig for the experiment by running the following code:

You plan to use this configuration to run a script that trains a random forest model and then tests it with validation data. The label values for the validation data are stored in a variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted.

You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric.

Solution: Run the following code:

Does the solution meet the goal?

Yes

52. DRAG DROP

You train and register a model by using the Azure Machine Learning SDK on a local workstation.

Python 3.6 and Visual Studio Code are installed on the workstation.

When you try to deploy the model into production as an Azure Kubernetes Service (AKS)-based web service, you experience an error in the scoring script that causes deployment to fail.

You need to debug the service on the local workstation before deploying the service to production.

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.

53. You manage an Azure Machine learning workspace.

You build a custom model you must log with Mlftow.

The custom model includes the following:

• The model is not natively supported by Mlflow.

• The model cannot be serialized in Pickle format.

• The model source code is complex.

• The Python library tor the model must be packaged with the model.

You need to create a custom model flavor to enable logging with ML. flow.

What should you use?

model loader

custom signatures

model wrapper

artifacts

54. 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 creating a new experiment in Azure Learning learning Studio.

One class has a much smaller number of observations than the other classes in the training

You need to select an appropriate data sampling strategy to compensate for the class imbalance.

Solution: You use the Synthetic Minority Oversampling Technique (SMOTE) sampling mode.

Does the solution meet the goal?

Yes

55. HOTSPOT

Your Azure Machine Learning workspace has a dataset named real_estate_data.

A sample of the data in the dataset follows.

You want to use automated machine learning to find the best regression model for predicting the price column.

You need to configure an automated machine learning experiment using the Azure Machine Learning SDK.

How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

56. You use Azure Machine Learning studio to analyze a dataset containing a decimal column named column1. You need to verity that the column1 values are normally distributed.

Which static should you use?

Profile

Type

Max

Mean

57. You use differential privacy to ensure your reports are private. The calculated value of the epsilon for your data is 1.8. You need to modify your data to ensure your reports are private.

Which epsilon value should you accept for your data?

between 0 and 1

between 2 and 3

between 3 and 10

more than 10

58. 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 using Azure Machine Learning to run an experiment that trains a classification model.

You want to use Hyperdrive to find parameters that optimize the AUC metric for the model.

You configure a HyperDriveConfig for the experiment by running the following code:

variable named y_test variable, and the predicted probabilities from the model are stored in a variable named y_predicted. You need to add logging to the script to allow Hyperdrive to optimize hyperparameters for the AUC metric.

Solution: Run the following code:

Does the solution meet the goal?

Yes

59. You create an Azure Machine Learning workspace.

You must configure an event-driven workflow to automatically trigger upon completion of training runs in the workspace. The solution must minimize the administrative effort to configure the trigger.

You need to configure an Azure service to automatically trigger the workflow.

Which Azure service should you use?

Event Grid subscription

Azure Automation runbook

Event Hubs Capture

Event Hubs consumer

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

Which technique should you use?

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

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

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

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

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61. You use the Two-Class Neural Network module in Azure Machine Learning Studio to build a binary

classification model. You use the Tune Model Hyperparameters module to tune accuracy for the model.

You need to select the hyperparameters that should be tuned using the Tune Model Hyperparameters module.

Which two hyperparameters should you use? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

Number of hidden nodes

Learning Rate

The type of the normalizer

Number of learning iterations

Hidden layer specification

62. You create an Azure Machine Learning workspace and a dataset. The dataset includes age values for a large group of diabetes patients. You use the dp.mean function from the SmartNoise library to calculate the mean of the age value. You store the value in a variable named age.mean.

You must output the value of the interval range of released mean values that will be returned 95 percent of the time.

You need to complete the code.

Which code values should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

63. 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?

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 namesales_dataset each month, replacing the existing dataset and specifying a tag named month indicating the month and year it was registered. Use this dataset for all experiments.

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

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.

Create a tabular dataset that references the datastore and explicitly specifies each 'sales/mm-yyyy/ sales.csv' file. Register the dataset with the namesales_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.

64. You need to select a pre built development environment for a series of data science experiments. You must use the R language for the experiments.

Which three environments can you use? Each correct answer presents a complete solution. NOTE:

Each correct selection is worth one point.

NET Library on a local environment

Azure Machine Learning Studio

Data Science Virtual Machine (OSVM)

Azure Data bricks

Azure Cognitive Services

65. You create an Azure Machine Learning workspace.

You must configure an event handler to send an email notification when data drift is detected in the workspace datasets. You must minimize development efforts.

You need to configure an Azure service to send the notification.

Which Azure service should you use?

Azure Function apps

Azure DevOps pipeline

Azure Automation runbook

Azure Logic Apps

66. You have a Python script that executes a pipeline.

The script includes the following code:

from azureml.core import Experiment

pipeline_run = Experiment(ws, 'pipeline_test').submit(pipeline)

You want to test the pipeline before deploying the script.

You need to display the pipeline run details written to the STDOUT output when the pipeline completes.

Which code segment should you add to the test script?

pipeline_run.get.metrics()

pipeline_run.wait_for_completion(show_output=True)

pipeline_param = PipelineParameter(name="stdout", default_value="console")

pipeline_run.get_status()

67. DRAG DROP

You use a training pipeline in the Azure Machine Learning designer. You register a datastore named ds1. The datastore contains multiple training data files. You use the Import Data module with the configured datastore.

You need to retrain a model on a different set of data files.

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.

68. HOTSPOT

You plan to implement a two-step pipeline by using the Azure Machine Learning SDK for Python.

The pipeline will pass temporary data from the first step to the second step.

You need to identify the class and the corresponding method that should be used in the second step to access temporary data generated by the first step in the pipeline.

Which class and method should you identify? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point

69. HOTSPOT

You create an Azure Machine Learning workspace. You train a classification model by using automated machine learning (automated ML) in Azure Machine Learning studio. The training data contains multiple classes that have significantly different numbers of samples.

You must use a metric type to avoid labeling negative samples as positive and an averaging method that will minimize the class imbalance.

You need to configure the metric type and the averaging method.

Which configurations should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

70. You create an Azure Machine Learning workspace. The workspace contains a dataset named sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline that will prepare data in the dataset and then train and register a model based on the prepared data.

The first stage of the pipeline contains the following code:

You need to identify the location containing the output of the first stage of the script that you can use as input for the second stage.

Which storage location should you use?

workspaceblobstore datastore

workspacefi lest ore datastore

compute instance

Page 8 of 12

71. You use the Azure Machine Learning service to create a tabular dataset named training.dat a. 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)

Option A

Option B

Option C

Option D

72. 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 False.

Set the value of the token_auth_enabled property to True.

Deploy the model to the service.

Does the solution meet the goal?

Yes

73. HOTSPOT

You must use in 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.

74. You create a multi-class image classification deep learning model that uses a set of labeled images. You create a script file named train.py that uses the PyTorch 1.3 framework to train the model.

You must run the script by using an estimator. The code must not require any additional Python libraries to be installed in the environment for the estimator. The time required for model training must be minimized.

You need to define the estimator that will be used to run the script.

Which estimator type should you use?

TensorFlow

PyTorch

SKLearn

Estimator Which values should you use in the REST request and to expect in the response? To answer, select the

75. You train and register an Azure Machine Learning model

You plan to deploy the model to an online endpoint

You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.

Solution:

Create a managed online endpoint with the default authentication settings. Deploy the model to the online endpoint.

Does the solution meet the goal?

Yes

76. You are planning to register a trained model in an Azure Machine Learning workspace.

You must store additional metadata about the model in a key-value format. You must be able to add new metadata and modify or delete metadata after creation.

You need to register the model.

Which parameter should you use?

description

model_framework

cags

properties

77. HOTSPOT

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.

78. 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?

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

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

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

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

79. 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 plan to use a Python script to run an Azure Machine Learning experiment. The script creates a reference to the experiment run context, loads data from a file, identifies the set of unique values for the label column, and completes the experiment run:

from azureml.core import Run

import pandas as pd

run = Run.get_context()

data = pd.read_csv('data.csv')

label_vals = data['label'].unique()

# Add code to record metrics here

run.complete()

The experiment must record the unique labels in the data as metrics for the run that can be reviewed later.

You must add code to the script to record the unique label values as run metrics at the point indicated by the comment.

Solution: Replace the comment with the following code:

run.log_list('Label Values', label_vals)

Does the solution meet the goal?

Yes

80. You register a file dataset named csvjolder that references a folder. The folder includes multiple com ma-separated values (CSV) files in an Azure storage blob container. You plan to use the following code to run a script that loads data from the file dataset.

You create and instantiate the following variables:

You have the following code:

You need to pass the dataset to ensure that the script can read the files it references.

Which code segment should you insert to replace the code comment?

inputs=[file_dataset.as_named_input('training_files').to_pandas_dataframe()],

inputs=[file_dataset.as_named_input('training_files').as_mount()],

script_params={'--training_files': file_dataset},

inputs=[file_dataset.as_named_input('training_files')],

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81. You create an Azure Machine Learning workspace named workspaces. You create a Python SDK v2 notebook to perform custom model training in workspace1. You need to run the notebook from Azure Machine Learning Studio in workspace1.

What should you provision first?

default storage account

real-time endpoint

Azure Machine Learning compute cluster

Azure Machine Learning compute instance

82. 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?

Coefficient of determination

Recall

Precision

Mean absolute error

Root Mean Square Error

83. You create and register a model in an Azure Machine Learning workspace.

You must use the Azure Machine Learning SDK to implement a batch inference pipeline that uses a ParallelRunStep to score input data using the model. You must specify a value for the ParallelRunConfig compute_target setting of the pipeline step.

You need to create the compute target.

Which class should you use?

BatchCompute

AdlaCompute

AmlCompute

Aks Compute

84. You create a classification model with a dataset that contains 100 samples with Class A and 10,000 samples with Class B

The variation of Class B is very high.

You need to resolve imbalances.

Which method should you use?

Partition and Sample

Cluster Centroids

Tomek links

Synthetic Minority Oversampling Technique (SMOTE)

85. You use the Azure Machine Learning Python SDK to define a pipeline to train a model.

The data used to train the model is read from a folder in a datastore.

You need to ensure the pipeline runs automatically whenever the data in the folder changes.

What should you do?

Set the regenerate_outputs property of the pipeline to True

Create a ScheduleRecurrance object with a Frequency of auto. Use the object to create a Schedule for the pipeline

Create a PipelineParameter with a default value that references the location where the training data is stored

Create a Schedule for the pipeline. Specify the datastore in the datastore property, and the folder containing the training data in the path_on_datascore property

86. HOTSPOT

You register the following versions of a model.

You use the Azure ML Python SDK to run a training experiment. You use a variable named run to reference the experiment run.

After the run has been submitted and completed, you run the following 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.

87. You manage an Azure Machine Learning workspace. You have an environment for training jobs which uses an existing Docker image. A new version of the Docker image is available.

You need to use the latest version of the Docker image for the environment configuration by using the Azure Machine Learning SDK v2-What should you do?

Modify the conda.file to specify the new version of the Docker image.

Use the Environment class to create a new version of the environment.

Use the create.or.update method to change the tag of the image.

Change the description parameter of the environment configuration.

88. You plan to use a Data Science Virtual Machine (DSVM) with the open source deep learning frameworks Caffe2 and Theano. You need to select a pre configured DSVM to support the framework.

What should you create?

Data Science Virtual Machine for Linux (CentOS)

Data Science Virtual Machine for Windows 2012

Data Science Virtual Machine for Windows 2016

Geo AI Data Science Virtual Machine with ArcGIS

Data Science Virtual Machine for Linux (Ubuntu)

89. HOTSPOT

You are using the Azure Machine Learning Service to automate hyperparameter exploration of your neural network classification model.

You must define the hyperparameter space to automatically tune hyperparameters using random sampling according to following requirements:

✑ The learning rate must be selected from a normal distribution with a mean value of 10 and a standard deviation of 3.

✑ Batch size must be 16, 32 and 64.

✑ Keep probability must be a value selected from a uniform distribution between the range of 0.05 and 0.1.

You need to use the param_sampling method of the Python API for the Azure Machine Learning Service.

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.

90. HOTSPOT

You are creating data wrangling and model training solutions in an Azure Machine Learning workspace.

You must use the same Python notebook to perform both data wrangling and model training.

You need to use the Azure Machine Learning Python SDK v2 to define and configure the Synapse Spark pool asynchronously in the workspace as dedicated compute

How should you complete the rode segment? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Page 10 of 12

91. HOTSPOT

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.

92. HOTSPOT

You are using the Hyperdrive feature in Azure Machine Learning to train a model.

You configure the Hyperdrive experiment by running the following 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.

93. 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?

Yes

94. 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?

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

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

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

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

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

95. You are solving a classification task.

The dataset is imbalanced.

You need to select an Azure Machine Learning Studio module to improve the classification accuracy.

Which module should you use?

Fisher Linear Discriminant Analysis.

Filter Based Feature Selection

Synthetic Minority Oversampling Technique (SMOTE)

Permutation Feature Importance

96. 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 an Azure Machine Learning model.

You plan to deploy the model to an online endpoint.

You need to ensure that applications will be able to use the authentication method with a non-expiring artifact to access the model.

Solution:

Create a managed online endpoint and set the value of its auto_mode parameter to key. Deploy the model to the inline endpoint.

Does the solution meet the goal?

Yes

97. HOTSPOT

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

Each correct selection is worth one point.

98. 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 creating a new experiment in Azure Machine Learning Studio.

One class has a much smaller number of observations than the other classes in the training set.

You need to select an appropriate data sampling strategy to compensate for the class imbalance.

Solution: You use the Scale and Reduce sampling mode.

Does the solution meet the goal?

Yes

99. You are building recurrent neural network to perform a binary classification.

The training loss, validation loss, training accuracy, and validation accuracy of each training epoch has been provided. You need to identify whether the classification model is over fitted.

Which of the following is correct?

The training loss increases while the validation loss decreases when training the model.

The training loss decreases while the validation loss increases when training the model.

The training loss stays constant and the validation loss decreases when training the model.

The training loss .stays constant and the validation loss stays on a constant value and close to the training loss value when training the model.

100. 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 creating a model to predict the price of a student’s artwork depending on the following variables: the student’s length of education, degree type, and art form.

You start by creating a linear regression model.

You need to evaluate the linear regression model.

Solution: Use the following metrics: Mean Absolute Error, Root Mean Absolute Error, Relative Absolute Error, Accuracy, Precision, Recall, F1 score, and AUC.

Does the solution meet the goal?

Yes

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101. DRAG DROP

You create an Azure Machine Learning workspace. You are training a classification model with no-code AutoML in Azure Machine Learning studio.

The model must predict if a client of a financial institution will subscribe to a fixed-term deposit. You must identify the feature that has the most influence on the predictions of the model for the second highest scoring algorithm. You must minimize the effort and time to identify the feature.

You need to complete the identification.

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.

102. DRAG DROP

You previously deployed a model that was trained using a tabular dataset named training-dataset, which is based on a folder of CSV files.

Over time, you have collected the features and predicted labels generated by the model in a folder containing a CSV file for each month. You have created two tabular datasets based on the folder containing the inference data: one named predictions-dataset with a schema that matches the training data exactly, including the predicted label; and another named features-dataset with a schema containing all of the feature columns and a timestamp column based on the filename, which includes the day, month, and year.

You need to create a data drift monitor to identify any changing trends in the feature data since the model was trained. To accomplish this, you must define the required datasets for the data drift monitor.

Which datasets should you use to configure the data drift monitor? To answer, drag the appropriate datasets to the correct data drift monitor options. Each source 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.

103. HOTSPOT

You publish a batch inferencing pipeline that will be used by a business application.

The application developers need to know which information should be submitted to and returned by the REST interface for the published pipeline.

You need to identify the information required in the REST request and returned as a response from the published pipeline.

Which values should you use in the REST request and to expect in the response? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

104. You are performing a filter based feature selection for a dataset 10 build a multi class classifies by using Azure Machine Learning Studio.

The dataset contains categorical features that are highly correlated to the output label column.

You need to select the appropriate feature scoring statistical method to identify the key predictors.

Which method should you use?

Chi-squared

Spearman correlation

Kendall correlation

Person correlation

105. You need to select a feature extraction method.

Which method should you use?

Mutual information

Mood’s median test

Kendall correlation

Permutation Feature Importance

106. HOTSPOT

You use Azure Machine Learning to implement hyperparameter tuning for an Azure ML Python SDK v2-based model training.

Training runs must terminate when the primary metric is lowered by 25 percent or more compared to the best performing run.

You need to configure an early termination policy to terminate training jobs.

Which values should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

107. HOTSPOT

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.

108. You use Azure Machine Learning Studio to build a machine learning experiment.

You need to divide data into two distinct datasets.

Which module should you use?

Partition and Sample

Assign Data to Clusters

Group Data into Bins

Test Hypothesis Using t-Test

109. HOTSPOT

You create an Azure Machine Learning workspace named workspace1. You assign a custom role to a user of workspace1.

The custom role has the following JSON definition:

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.

110. DRAG DROP

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.

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111. You have the following Azure subscriptions and Azure Machine Learning service workspaces:

You need to obtain a reference to the ml-project workspace.

Solution: Run the following Python code:

Does the solution meet the goal?

Yes

112. 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 create an Azure Machine Learning service datastore in a workspace.

The datastore contains the following files:

• /data/2018/Q1.csv

• /data/2018/Q2.csv

• /data/2018/Q3.csv

• /data/2018/Q4.csv

• /data/2019/Q1.csv

All files store data in the following format:

id,f1,f2i

1,1.2,0

2,1,1,

1 3,2.1,0

You run the following code:

You need to create a dataset named training_data and load the data from all files into a single data frame by using the following code:

Solution: Run the following code:

Does the solution meet the goal?

Yes

113. you create an Azure Machine learning workspace named workspace1. The workspace contains a Python SOK v2 notebook mat uses Mallow to correct model coaxing men’s anal arracks from your local computer.

Vou must reuse the notebook to run on Azure Machine I earning compute instance m workspace.

You need to comminute to log training and artifacts from your data science code.

What should you do?

Configure the tracking UR

Instantiate the MLClient class.

Instantiate the job class.

114. You are creating a binary classification by using a two-class logistic regression model.

You need to evaluate the model results for imbalance.

Which evaluation metric should you use?

Relative Absolute Error

AUC Curve

Mean Absolute Error

Relative Squared Error

115. You create a datastore named training_data that references a blob container in an Azure Storage account. The blob container contains a folder named csv_files in which multiple comma-separated values (CSV) files are stored.

You have a script named train.py in a local folder named ./script that you plan to run as an experiment using an estimator.

The script includes the following code to read data from the csv_files folder:

You have the following script.

You need to configure the estimator for the experiment so that the script can read the data from a data reference named data_ref that references the csv_files folder in the training_data datastore.

Which code should you use to configure the estimator?

A)