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

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 a model to forecast weather conditions based on historical data.

You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.

Solution: Run the following code:

Does the solution meet the goal?

You are developing a machine learning model by using Azure Machine Learning. You are using multiple text files in tabular format for model data. You have the following requirements:

• You must use AutoML jobs to train the model.

• You must use data from specified columns.

• The data concept must support lazy evaluation.

You need to load data into a Pandas dataframe.

Which data concept should you use?

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.

You use the Azure Machine Learning SDK to run a training experiment that trains a classification model and calculates its accuracy metric.

The model will be retrained each month as new data is available.

You must register the model for use in a batch inference pipeline.

You need to register the model and ensure that the models created by subsequent retraining experiments are registered only if their accuracy is higher than the currently registered model.

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

NOTE: Each correct selection is worth one point.

You are building a regression model tot estimating the number of calls during an event.

You need to determine whether the feature values achieve the conditions to build a Poisson regression model.

Which two conditions must the feature set contain? I ach correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning workspace. The Pylhon scrip! named scriptpy reads an argument named training_data. The trainlng.data argument specifies the path to the training data in a file named datasetl.csv.

You plan to run the scriptpy Python script as a command job that trains a machine learning model.

You need to provide the command to pass the path for the datasct as a parameter value when you submit the script as a training job.

Solution: python train.py --training_data training_data

Does the solution meet the goal?

You are developing a machine learning solution by using the Azure Machine Learning designer.

You need to create a web service that applications can use to submit data feature values and retrieve a predicted label.

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.

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?

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:

for label_val in label_vals:

run.log('Label Values', label_val)

Does the solution meet the goal?

You manage an Azure Machine Learning workspace. You create an experiment named experiment1 by using the Azure Machine Learning Python SDK v2 and MLflow. You are reviewing the results of experiment1 by using the following code segment:

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

You manage an Azure Machine Learning workspace. The development environment tor managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks A Synapse Spark Compute is currently attached and uses system-assigned identity You need to use Python code to update the Synapse Spark Compute 10 use a user-assigned identity.

Solution: Configure the IdentityConfiguration class with the appropriate identity type.

Does the solution meet the goal?

You plan to use automated machine learning by using Azure Machine Learning Python SDK v2 to train a regression model. You have data that has features with missing values, and categorical features with few distinct values.

You need to control whether automated machine learning automatically imputes missing values and encode categorical features as part of the training task. Which enemy of the autumn package should you use?

You manage an Azure Machine Learning workspace named workspace1by using the Python SDK v2.

You must register datastores in workspace 1 for Azure Blot storage and Azure Fetes storage to meet the following requirements.

* Azure Active Directory (Azure AD) authentication must be used for access to storage when possible.

* Credentials and secrets steed in workspace1 must be valid lot a specified time period when accessing Azure Files storage.

You need to configure a security access method used to register the Azure Blob and azure files storage in workspace1.

Which security access method should you configure? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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.

You manage an Azure Al Foundry project. You build a multi-turn chatbot application.

You plan to filter your traces to identity issues while observing how the application is responding. The solution must not use an external knowledge base. You need to select an evaluation metric. Which built-in evaluator should you use?

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 use Azure Machine Learning designer to load the following datasets into an experiment:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Join Data module.

Does the solution meet the goal?

You have an Azure Al Foundry project that contains a flow. The flow includes two nodes; Node1 and Node2.

You plan to create three variants for each of the nodes and test how well different variants work for each node

You need to submit flow runs from Azure Al Foundry and evaluate the resulting variant runs.

What is the minimum number of runs you should plan for? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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

You need to ensure that you can use MLflow Tracking with Azure Machine Learning Python SDK v2 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.

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 contains 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: Replace each missing value using the Multiple Imputation by Chained Equations (MICE) method.

Does the solution meet the goal?

You are a data scientist building a deep convolutional neural network (CNN) for image classification.

The CNN model you built shows signs of overfitting.

You need to reduce overfitting and converge the model to an optimal fit.

Which two actions should you perform? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

You have an Azure Machine Learning workspace.

You plan to use the workspace to set up automated machine learning training for an image classification model.

You need to choose the primary metric to optimize the model training.

Which primary metric should you choose?

You train a machine learning model.

You must deploy the model as a real-time inference service for testing. The service requires low CPU utilization and less than 48 MB of RAM. The compute target for the deployed service must initialize automatically while minimizing cost and administrative overhead.

Which compute target should you use?

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.

You have an Azure Machine Learning workspace.

You plan to tune a model hyperparameter when you train the model.

You need to define a search space that returns a normally distributed value.

Which parameter should you use?

You use Azure Machine Learning Designer lo load the following datasets into an experiment:

Dataset1:

Dataset2:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Add Rows component.

Does the solution meet the goal?

You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model.

You must use Hyperdrive to try combinations of the following hyperparameter values:

• learning_rate: any value between 0.001 and 0.1

• batch_size: 16, 32, or 64

You need to configure the search space for the Hyperdrive experiment.

Which two parameter expressions should you use? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

You create a workspace to include a compute instance by using Azure Machine Learning Studio. You are developing a Python SDK v2 notebook in the workspace. You need to use Intellisense in the notebook. What should you do?

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.

: 212

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?

You arc I mating a deep learning model to identify cats and dogs. You have 25,000 color images.

You must meet the following requirements:

• Reduce the number of training epochs.

• Reduce the size of the neural network.

• Reduce over-fitting of the neural network.

You need to select the image modification values.

Which value should you use? To answer, select the appropriate Options in the answer area.

NOTE: Each correct selection is worth one point.

You create a pipeline in designer to train a model that predicts automobile prices.

Because of non-linear relationships in the data, the pipeline calculates the natural log (Ln) of the prices in the training data, trains a model to predict this natural log of price value, and then calculates the exponential of the scored label to get the predicted price.

The training pipeline is shown in the exhibit. (Click the Training pipeline tab.)

Training pipeline

You create a real-time inference pipeline from the training pipeline, as shown in the exhibit. (Click the Real-time pipeline tab.)

Real-time pipeline

You need to modify the inference pipeline to ensure that the web service returns the exponential of the scored label as the predicted automobile price and that client applications are not required to include a price value in the input values.

Which three modifications must you make to the inference pipeline? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

You design a project for interactive data mangling with Apache Spark in an Azure Machine Learning workspace. The data pipeline must provide the following solution:

• Ingest and process a vast amount of data from various sources and linked services, such as databases and APIs

• Visualize the results in Microsoft Power Bl.

• Include a possibility to quickly identify and address issues by observing only a small amount of data using the fewest resources.

You need to select a computation option for project activities.

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?

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?

You create a workspace by using Azure Machine Learning Studio.

You must run a Python SDK v2 notebook in the workspace by using Azure Machine Learning Studio.

You need to reset the state of the notebook.

Which three actions should you use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

You manage an Azure Machine learning workspace. You develop a machine teaming model.

You are deploying the model to use a low-pointy VM mm a pacing discount.

You need to deploy the model.

Which compute large! should you use?

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?

You are authoring a notebook in Azure Machine Learning studio.

You must install packages from the notebook into the currently running kernel. The installation must be limited to the currently running kernel only.

You need to install the packages.

Which magic function should you use?

You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model.

You must use Hyperdrive to try combinations of the following hyperparameter values. You must not apply an early termination policy.

learning_rate: any value between 0.001 and 0.1

• batch_size: 16, 32, or 64

You need to configure the sampling method for the Hyperdrive experiment

Which two sampling methods can you use? Each correct answer is a complete solution.

NOTE: Each correct selection is worth one point.

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.

You need to implement source control for scripts in an Azure Machine Learning workspace. You use a terminal window in the Azure Machine Learning Notebook tab

You must authenticate your Git account with SSH.

You need to generate a new SSH key.

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 m the correct order.

You must store data in Azure Blob Storage to support Azure Machine Learning.

You need to transfer the data into Azure Blob Storage.

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

NOTE: Each correct selection is worth one point.

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 preview the data profile in Azure Machine Learning studio once the dataset is created.

You need to train the model.

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.

You create an Azure Machine Learning workspace. You train an MLflow-formatted regression model by using tabular structured data.

You must use a Responsible Al dashboard to assess the model.

You need to use the Azure Machine Learning studio Ul to generate the Responsible A dashboard.

What should you do first?

: 211

You create an Azure Machine Learning workspace.

You must create a custom role named DataScientist that meets the following requirements:

Role members must not be able to delete the workspace.

Role members must not be able to create, update, or delete compute resource in the workspace.

Role members must not be able to add new users to the workspace.

You need to create a JSON file for the DataScientist role in the Azure Machine Learning workspace.

The custom role must enforce the restrictions specified by the IT Operations team.

Which JSON code segment should you use?

A)

B)

C)

D)

You use Azure Machine Learning to train a model.

You must use a sampling method for tuning hyperparameters. The sampling method must pick samples based on how the model performed with previous samples.

You need to select a sampling method.

Which sampling method should you use?

You ate reviewing model benchmarks in Azure Al Foundry.

You must use a large language model based on the proficiency of the model to generate the most linguistically correct text. You need to select the model benchmark. Which benchmark metric should you focus on?

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.

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.

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.

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

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.

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

What should you do?

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.

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?

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.

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

Which technique should you use?

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.

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

Which environment should you use?

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

Which normalization type should you use?

You need to select a feature extraction method.

Which method should you use?

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.

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.

You need to select a feature extraction method.

Which method should you use?

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.

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.

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.

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.

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.

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.

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.

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.

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.