TRAINING TEST

Question
Which type of artificial intelligence (AI) workload provides the ability to
generate bounding boxes that identify the locations of different types of
vehicles in an image?

Correct Answer
● object detection

This answer is correct.

Object detection provides the ability to generate bounding boxes

identifying the locations of different types of vehicles in an image. The
other answer choices also process images, but their outcomes are
different.
Understand computer vision - Training | Microsoft Learn

_________________________

Question
Which type of service provides a platform for conversational artificial
intelligence (AI)?

Correct Answer
● Azure AI Bot Service

This answer is correct.

Azure AI Bot Service provide a platform for conversational artificial

intelligence (AI), which designates the ability of software agents to
participate in a conversation. Azure AI Translator is part of Natural
language processing (NLP), but it does not serve as a platform for
conversational AI. Azure AI Vision deals with image processing. Azure AI
Document Intelligence extracts information from scanned forms and
invoices.
Understand natural language processing - Training | Microsoft Learn

_________________________

Question
Which artificial intelligence (AI) workload scenario is an example of
anomaly detection?

Correct Answer
● monitoring the flow speed and low/high points of river water levels

This answer is correct.

Anomaly detection can be used to detect unusual fluctuations in river

water flows and levels through time-series sensor data. Monitoring traffic
to identify vehicle types is a computer vision workload that can classify
images based on their contents. A chatbot is a natural language
processing (NLP) workload. Using a search solution to extract information
from a range of sources is a knowledge mining workload.
Introduction to Anomaly Detector - Training | Microsoft Learn

_________________________

Question
Which artificial intelligence (AI) workload scenario is an example of natural
language processing (NLP)?

Correct Answer
● extracting key phrases from a business insights report

This answer is correct.

Extracting key phrases from text to identify the main terms is an NLP
workload. Predicting whether customers are likely to buy a product based
on previous purchases requires the development of a machine learning
model. Monitoring for sudden increases in quantity of failed sign-in
attempts is an anomaly detection workload. Identifying objects in
landscape images is a computer vision workload.
Analyze text with the Language service - Training | Microsoft Learn

_________________________

Question
Which two artificial intelligence (AI) workload scenarios are examples of
natural language processing (NLP)? Each correct answer presents a
complete solution.

Correct Answer
● performing sentiment analysis on social media data

This answer is correct.

 ● translating text between different languages from product reviews
This answer is correct.

Translating text between different languages from product reviews is an

NLP workload that uses the Azure AI Translator service and is part of
Azure AI Services. It can provide text translation of supported languages
in real time. Performing sentiment analysis on social media data is an NLP
that uses the sentiment analysis feature of the Azure AI Service for
Language. It can provide sentiment labels, such as negative, neutral, and
positive for text-based sentences and documents.
Microsoft Azure AI Fundamentals: Explore natural language processing -
Training | Microsoft Learn

_________________________

Question
Which principle of responsible artificial intelligence (AI) raises awareness
about the limitations of AI-based solutions?

Correct Answer
● transparency

This answer is correct.

Transparency provides clarity regarding the purpose of AI solutions, the

way they work, as well as their limitations. The privacy and security,
reliability and safety, and accountability principles focus on the
capabilities of AI, rather than raising awareness about its limitations.
Understand Responsible AI - Training | Microsoft Learn
Identify principles and practices for responsible AI - Training | Microsoft
Learn

_________________________

Question
Which principle of responsible artificial intelligence (AI) has the objective
of ensuring that AI solutions benefit all parts of society regardless of
gender or ethnicity?

Correct Answer
● inclusiveness

This answer is correct.

The inclusiveness principle is meant to ensure that AI solutions empower
and engage everyone, regardless of criteria such as physical ability,
gender, sexual orientation, or ethnicity. Privacy and security, reliability and
safety, and accountability do not discriminate based on these criteria, but
also do not emphasize the significance of bringing benefits to all parts of
the society.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
Which principle of responsible artificial intelligence (AI) plays the primary
role when implementing an AI solution that meet qualifications for
business loan approvals?

Correct Answer
● fairness

This answer is correct.

Fairness is meant to ensure that AI models do not unintentionally

incorporate a bias based on criteria such as gender or ethnicity.
Transparency does not apply in this case since banks commonly use their
proprietary models when processing loan approvals. Inclusiveness is also
out of scope since not everyone is qualified for a loan. Safety is not a
primary consideration since there is no direct threat to human life or
health in this case.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
A bank is developing a new artificial intelligence (AI) system to support
the process of accepting or rejecting mortgage applications.
Which two issues should be considered as part of the responsible AI
principle of fairness to avoid biased decision making? Each correct answer
presents part of the solution.

Correct Answer
● ethnicity

This answer is correct.

● gender
This answer is correct.
 ●

The AI system must be designed to ensure that biased decision making is

avoided and not based on factors such as ethnicity and gender. The
system will consider salary, payment history, and credit utilization. These
are standard metrics.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
Which two principles of responsible artificial intelligence (AI) are most
important when designing an AI system to manage healthcare data? Each
correct answer presents part of the solution.

Correct Answer
● accountability

This answer is correct.

● privacy and security

This answer is correct.

The accountability principle states that AI systems are designed to meet

any ethical and legal standards that are applicable. The system must be
designed to ensure that privacy of the healthcare data is of the highest
importance, including anonymizing data where applicable. The fairness
principle is applied to AI systems to ensure that users of the systems are
treated fairly. The inclusiveness principle states that AI systems must
empower people in a positive and engaging way.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
A company is currently developing driverless agriculture vehicles to help
harvest crops. The vehicles will be deployed alongside people working in
the crop fields, and as such, the company will need to carry out robust
testing.
Which principle of responsible artificial intelligence (AI) is most important
in this case?

Correct Answer
● reliability and safety

This answer is correct.

 ●

The reliability and safety principles are of paramount importance here as it

requires an AI system to work alongside people in a physical environment
by using AI controlled machinery. The system must function safely, while
ensuring no harm will come to human life.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
Which type of machine learning algorithm groups observations is based
on the similarities of features?

Correct Answer
● clustering

This answer is correct.

Clustering algorithms group data points that have similar characteristics.

Regression algorithms are used to predict numeric values. Classification
algorithms are used to predict a predefined category to which an input
value belongs. Supervised learning is a category of learning algorithms
that includes regression and classification, but not clustering.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn
What are classification models? - Training | Microsoft Learn
What is clustering? - Training | Microsoft Learn

_________________________

Question
Predicting rainfall for a specific geographical location is an example of
which type of machine learning?

Correct Answer
● regression

This answer is correct.

Predicting rainfall is an example of regression machine learning, as it will

predict a numeric value for future rainfall by using historical time-series
rainfall data based on factors, such as seasons. Clustering is a machine
learning type that analyzes unlabeled data to find similarities in the data.
Featurization is not a machine learning type, but a collection of
techniques, such as feature engineering, data-scaling, and normalization.
Classification is used to predict categories of data.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
A retailer wants to group together online shoppers that have similar
attributes to enable its marketing team to create targeted marketing
campaigns for new product launches.
Which type of machine learning is this?

Correct Answer
● clustering

This answer is correct.

Clustering is a machine learning type that analyzes unlabeled data to find

similarities present in the data. It then groups (clusters) similar data
together. In this example, the company can group online customers based
on attributes that include demographic data and shopping behaviors. The
company can then recommend new products to those groups of
customers who are most likely to be interested in them. Classification and
multiclass classification are used to predict categories of data. Regression
is a machine learning scenario that is used to predict numeric values.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
Which assumption of the multiple linear regression model should be
satisfied to avoid misleading predictions?

Correct Answer
● Features are independent of each other.

This answer is correct.

Multiple linear regression models the relationship between several

features and a single label. The features must be independent of each
other, otherwise, the model's predictions will be misleading.
Multiple linear regression and R-squared - Training | Microsoft Learn

_________________________
Question
Which feature makes regression an example of supervised machine
learning?

Correct Answer
● use of historical data with known label values to train a model

This answer is correct.

Regression is an example of supervised machine learning due to the use

of historical data with known label values to train a model. Regression
does not rely on randomly generated data for training.
What is regression? - Training | Microsoft Learn
What is clustering? - Training | Microsoft Learn

_________________________

Question
In a regression machine learning algorithm, what are the characteristics of
features and labels in a validation dataset?

Correct Answer
● known feature and label values

This answer is correct.

In a regression machine learning algorithm, a validation set contains

known feature and label values.
What is regression? - Training | Microsoft Learn

_________________________

Question
In a regression machine learning algorithm, what are the characteristics of
features and labels in a training dataset?

Correct Answer
● known feature and label values

This answer is correct.

In a regression machine learning algorithm, a training set contains known

feature and label values.
What is regression? - Training | Microsoft Learn
_________________________

Question
A company is using machine learning to predict various aspects of its e-
scooter hire service dependent on weather. This includes predicting the
number of hires, the average distance traveled, and the impact on e-
scooter battery levels.
For the machine learning model, which two attributes are the features?
Each correct answer presents a complete solution.

Correct Answer
● distance traveled

This answer is correct.

● e-scooter hires
This answer is correct.

Weather temperature and weekday or weekend are features that provide a

weather temperature for a given day and a value based on whether the
day is on a weekend or weekday. These are input variables for the model
to help predict the labels for e-scooter battery levels, number of hires,
and distance traveled. E-scooter battery levels, number of hires, and
distance traveled are numeric labels you are attempting to predict through
the machine learning model.
What is machine learning? - Training | Microsoft Learn

_________________________

Question
A company wants to predict household water use based on the number of
people in a house, the weather temperature, and the time of year.
In terms of data labels and features, what is the label in this use case?

Correct Answer
● water use

This answer is correct.

Water use is the label value that you want to predict, also known as the
independent variable. Number of people in the house, weather
temperature, and time of year are features, and are values that are
dependent on the label. Number of people in the house, weather
temperature, and time of year can influence the water consumed in a
household.
What is machine learning? - Training | Microsoft Learn

_________________________

Question
You need to use Azure Machine Learning to train a regression model.
What should you create in Machine Learning studio?

Correct Answer
● a job

This answer is correct.

A job must be created in Machine Learning studio to use Machine Learning

to train a regression model. A workspace must be created before you can
access Machine Learning studio. An Azure container instance and an AKS
cluster can be created as a deployment target, after training of a model is
complete.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn

_________________________

Question
You need to use the Azure Machine Learning designer to train a machine
learning model.
What should you do first in the Machine Learning designer?

Correct Answer
● Add a dataset.

This answer is correct.

Before you can start training a machine learning model, you must first
create a pipeline in the Machine Learning designer. This is followed by
adding a dataset, adding training modules, and eventually deploying a
service.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
You need to use the Azure Machine Learning designer to deploy a
predictive service from a newly trained model.
What should you do first in the Machine Learning designer?

Correct Answer
● Create an inference pipeline.

This answer is correct.

To deploy a predictive service from a newly trained model by using the

Machine Learning designer, you must first create a pipeline in the Machine
Learning designer. Adding training modules by using the Machine Learning
designer takes place before creating a trained model, which already
exists. Adding a dataset by using the Machine Learning designer requires
that a pipeline already exists. To create an inferencing cluster, you must
use Machine Learning studio.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
You train a regression model by using automated machine learning
(automated ML) in the Azure Machine Learning studio. You review the best
model summary.
You need to publish the model for others to use from the internet.
What should you do next?

Correct Answer
● Deploy the model to an endpoint.

This answer is correct.

You can deploy the best performing model for client applications to use
over the internet by using an endpoint. Compute clusters are used to train
the model and are created directly after you create a Machine Learning
workspace. Before you can test the model’s endpoint, you must deploy it
first to an endpoint. Automated ML performs the validation automatically,
so you do not need to split the dataset.
What is automated ML? AutoML - Azure Machine Learning | Microsoft
Learn
Understand steps for regression - Training | Microsoft Learn

_________________________

Question
Which three supervised machine learning models can you train by using
automated machine learning (automated ML) in the Azure Machine
Learning studio? Each correct answer presents a complete solution.

Correct Answer
● classification

This answer is correct.

● regression
This answer is correct.

● time-series forecasting
This answer is correct.

Time-series forecasting, regression, and classification are supervised

machine learning models. Automated ML learning can predict categories
or classes by using a classification algorithm, as well as numeric values as
part of the regression algorithm, and at a future point in time by using
time-series data. Inference pipeline is not a machine learning model.
Clustering is unsupervised machine learning and automated ML only
works with supervised learning algorithms.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn

_________________________

Question
Which machine learning algorithm module in the Azure Machine Learning
designer is used to train a model?

Correct Answer
● Linear Regression

This answer is correct.

Linear regression is a machine learning algorithm module used for training

regression models. The Clean Missing Data module is part of preparing
the data and data transformation process. Select Columns in Dataset is a
data transformation component that is used to choose a subset of
columns of interest from a dataset. Evaluate model is a component used
to measure the accuracy of trained models.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________
Question
Which artificial intelligence (AI) technique should be used to extract the
name of a store from a photograph displaying the store front?

Correct Answer
● optical character recognition (OCR)

This answer is correct.

OCR provides the ability to detect and read text in images. NLP is an area
of AI that deals with identifying the meaning of a written or spoken
language, but not detecting or reading text in images. Image classification
classifies images based on their contents. Semantic segmentation
provides the ability to classify individual pixels in an image.
Understand computer vision - Training | Microsoft Learn

_________________________

Question
Which two specialized domain models are supported by Azure AI Vision
when categorizing an image? Each correct answer presents a complete
solution.

Which two specialized domain models are supported by using the Azure
AI Vision service? Each correct answer presents a complete solution. [The
Azure AI Vision service supports the celebrities and landmarks specialized
domain models. It does not support specialized domain models for
animals, cars, or plants.]
Get started with image analysis on Azure - Training | Microsoft Learn

Correct Answer
● celebrities

This answer is correct.

● landmarks
This answer is correct.

When categorizing an image, the Azure AI Vision service supports two

specialized domain models: celebrities and landmarks. Image types is an
additional capability of the computer vision service, allowing it to detect
the type of image, such as a clip art image or a line drawing. Both people_
and people_group are supported categories when performing image
classification.
Get started with image analysis on Azure - Training | Microsoft Learn

_________________________

Question
Which computer vision service provides bounding coordinates as part of
its output?

Correct Answer
● object detection

This answer is correct.

Object detection provides the ability to generate bounding boxes that

identify the locations of different types of objects in an image, including
the bounding box coordinates, designating the location of the object in
the image. Semantic segmentation provides the ability to classify
individual pixels in an image. Image classification classifies images based
on their contents. Image analysis extracts information from the image to
label it with tags or captions.
Get started with image analysis on Azure - Training | Microsoft Learn
Understand computer vision - Training | Microsoft Learn

_________________________

Question
Which process allows you to use object detection?

Correct Answer
● tracking livestock in a field

This answer is correct.

Object detection can be used to track livestock animals, such as cows, to

support their safety and welfare. For example, a farmer can track whether
a particular animal has not been mobile. Sentiment analysis is used to
return a numeric value based on the analysis of a text. Employee access to
a secure building can be achieved by using facial recognition. Extracting
text from manuscripts is an example of a computer vision solution that
uses optical character recognition (OCR).
What is object detection? - Training | Microsoft Learn

_________________________

Question
What can be used for an attendance system that can scan handwritten
signatures?

Correct Answer
● optical character recognition (OCR)

This answer is correct.

OCR is used to extract text and handwriting from images. In this case, it
can be used to extract signatures for attendance purposes. Face
detection can detect and verify human faces, not text, from images.
Object detection can detect multiple objects in an image by using
bounding box coordinates. It is not used to extract handwritten text.
Image classification is the part of computer vision that is concerned with
the primary contents of an image.
Read text with the Computer Vision service - Training | Microsoft Learn

_________________________

Question
Which feature of computer vision involves associating an image with
metadata that summarizes the attributes of the image?

Correct Answer
● tagging

This answer is correct.

Tagging involves associating an image with metadata that summarizes the

attributes of the image. Detecting image types involves identifying clip art
images or line drawings. Content organization involves identifying people
or objects in photos and organizing them based on the identification.
Categorizing involves associating the contents of an image with a limited
set of categories.
Get started with image analysis on Azure - Training | Microsoft Learn

_________________________

Question
Which three parts of the machine learning process does the Azure AI
Vision eliminate the need for? Each correct answer presents part of the
solution.

Correct Answer
● choosing a model
 ●

This answer is correct.

● evaluating a model
This answer is correct.

● training a model
This answer is correct.

The computer vision service eliminates the need for choosing, training,
and evaluating a model by providing pre-trained models. To use computer
vision, you must create an Azure resource. The use of computer vision
involves inferencing.
Introduction - Training | Microsoft Learn

_________________________

Question
Which analytical task of the Azure AI Vision service returns bounding box
coordinates?

Correct Answer
● object detection

This answer is correct.

Detecting objects identifies common objects and, for each, returns

bounding box coordinates. Image categorization assigns a category to an
image, but it does not return bounding box coordinates. Tagging involves
associating an image with metadata that summarizes the attributes of the
image, but it does not return bounding box coordinates. OCR detects
printed and handwritten text in images, but it does not return bounding
box coordinates.
Get started with image analysis on Azure - Training | Microsoft Learn

_________________________

Question
Which two prebuilt models allow you to use the Azure AI Document
Intelligence service to scan information from international passports and
sales accounts? Each correct answer presents part of the solution.

Correct Answer
● ID document model

This answer is correct.

 ● invoice model
This answer is correct.

The invoice model extracts key information from sales invoices and is
suitable for extracting information from sales account documents. The ID
document model is optimized to analyze and extract key information from
US driver’s licenses and international passport biographical pages. The
business card model, receipt model, and language model are not suitable
to extract information from passports or sales account documents.
Analyze receipts with the Form Recognizer service - Training | Microsoft
Learn
Document processing models - Form Recognizer - Azure Applied AI
Services | Microsoft Learn

_________________________

Question
When using the Azure AI Face service, what should you use to perform
one-to-many or one-to-one face matching? Each correct answer presents
a complete solution.

Correct Answer
● face identification

This answer is correct.

● face verification
This answer is correct.

Face identification in the Azure AI Face service can address one-to-many

matching of one face in an image to a set of faces in a secure repository.
Face verification has the capability for one-to-one matching of a face in an
image to a single face from a secure repository or a photo to verify
whether they are the same individual. Face attributes, the find similar
faces operation, and Azure AI Custom Vision do not verify the identity of a
face.
What is the Azure Face service? - Azure Cognitive Services | Microsoft
Learn
Detect and analyze faces with the Face service - Training | Microsoft
Learn

_________________________
Question
Which natural language processing (NLP) technique assigns values to
words such as plant and flower, so that they are considered closer to each
other than a word such as airplane?

Correct Answer
● vectorization

This answer is correct.

Vectorization captures semantic relationships between words by assigning

them to locations in n-dimensional space. Lemmatization, also known as
stemming, normalizes words before counting them. Frequency analysis
counts how often a word appears in a text. N-grams extend frequency
analysis to include multi-term phrases.
Introduction - Training | Microsoft Learn

_________________________

Question
What is the first step in the statistical analysis of terms in a text in the
context of natural language processing (NLP)?

Correct Answer
● removing stop words

This answer is correct.

Removing stop words is the first step in the statistical analysis of terms
used in a text in the context of NLP. Counting the occurrences of each
word takes place after stop words are removed. Creating a vectorized
model is not part of statistical analysis. It is used to capture the sematic
relationship between words. Encoding words as numeric features is not
part of statistical analysis. It is frequently used in sentiment analysis.
Introduction - Training | Microsoft Learn

_________________________

Question
What is the confidence score returned by the Azure AI Language
detection service of natural language processing (NLP) for an unknown
language name?

Correct Answer
● NaN
 ●

This answer is correct.

NaN, or not a number, designates an unknown confidence score. Unknown

is a value with which the NaN confidence score is associated. The score
values range between 0 and 1, with 0 designating the lowest confidence
score and 1 designating the highest confidence score.
Get started with text analysis - Training | Microsoft Learn

_________________________

Question
Which Azure AI Service for Language feature can be used to analyze
online user reviews to identify whether users view a product positively or
negatively?

Correct Answer
● sentiment analysis

This answer is correct.

Sentiment analysis provides sentiment labels, such as negative, neutral,

and positive, based on a confidence score from text analysis. This makes
it suitable for understanding user sentiment for product reviews. The
named entity recognition, key phrase extraction, and language detection
features cannot perform sentiment analysis for product reviews.
Analyze text with the Language service - Training | Microsoft Learn
What is sentiment analysis and opinion mining in Azure Cognitive Service
for Language? - Azure Cognitive Services | Microsoft Learn

_________________________

Question
Which two features of Azure AI Services allow you to identify issues from
support question data, as well as identify any people and products that
are mentioned? Each correct answer presents part of the solution.

Correct Answer
● key phrase extraction

This answer is correct.

● named entity recognition

This answer is correct.

Key phrase extraction is used to extract key phrases to identify the main
concepts in a text. It enables a company to identify the main talking points
from the support question data and allows them to identify common
issues. Named entity recognition can identify and categorize entities in
unstructured text, such as people, places, organizations, and quantities.
The Azure AI Speech service, Conversational Language Understanding,
and Azure AI Bot Service are not designed for identifying key phrases or
entities.
Key Phrase Extraction cognitive skill – Azure Cognitive Search | Microsoft
Learn
Extract insights from text with the Language service – Training | Microsoft
Learn
Analyze text with the Language service – Training | Microsoft Learn

_________________________

Question
Which feature of the Azure AI Language service includes functionality that
returns links to external websites to disambiguate terms identified in a
text?

Correct Answer
● entity recognition

This answer is correct.

Entity recognition includes the entity linking functionality that returns links
to external websites to disambiguate terms (entities) identified in a text.
Key phrase extraction evaluates the text of a document and identifies its
main talking points. Azure AI Language detection identifies the language
in which text is written. Sentiment analysis evaluates text and returns
sentiment scores and labels for each sentence.
Get started with text analysis - Training | Microsoft Learn

_________________________

Question
Which three features are elements of the Azure AI Language Service?
Each correct answer presents a complete solution.

Correct Answer
● Entity Linking

This answer is correct.

● Personally Identifiable Information (PII) detection

 ●

This answer is correct.

● Sentiment analysis
This answer is correct.

Entity Linking, PII detection, and sentiment analysis are all elements of the
Azure AI Service for Azure AI Language. Azure AI Anomaly detection
monitors data over time to detect anomalies by using machine learning.
Azure AI Content Moderator is an Azure AI Services service that is used to
check text, image, and video content for material that is potentially
offensive.
What is Azure Cognitive Service for Language - Azure Cognitive Services |
Microsoft Learn
Microsoft Azure AI Fundamentals: Explore natural language processing -
Training | Microsoft Learn

_________________________

Question
Which three features are elements of the Azure AI Speech service? Each
correct answer presents a complete solution.

Correct Answer
● language identification

This answer is correct.

● speaker recognition
This answer is correct.

● voice assistants
This answer is correct.

Language identification, speaker recognition, and voice assistants are all

elements of the Azure AI Speech service. Text translation and document
translation are part of the Translator service.
What is the Speech service? - Azure Cognitive Services | Microsoft Learn
Recognize and synthesize speech - Training | Microsoft Learn

_________________________

Question
Which feature of the Azure AI Translator service is available only to
Custom Translator?
Correct Answer
● model training with a dictionary

This answer is correct.

Model training with a dictionary can be used with Custom Translator when
you do not have enough parallel sentences to meet the 10,000 minimum
requirements. The resulting model will typically complete training much
faster than with full training and will use the baseline models for
translation along with the dictionaries you have added.
What is Custom Translator? - Azure Cognitive Services | Microsoft Learn
Introduction to Translator - Training | Microsoft Learn

_________________________

Question
Which feature of the Azure AI Speech service can identify distinct user
voices?

Correct Answer
● speech recognition

This answer is correct.

Speech recognition uses audio data to analyze speech and determine

recognizable patterns that can be mapped to distinct user voices. Azure
AI Speech synthesis is concerned with vocalizing data, usually by
converting text to speech. Azure AI Speech translation is concerned with
multilanguage translation of speech. Language identification is used to
identify languages spoken in audio when compared against a list of
supported languages.
Speaker recognition overview - Speech service - Azure Cognitive Services
| Microsoft Learn
Recognize and synthesize speech - Training | Microsoft Learn

_________________________

Question
What is used to test a Language Understanding app model?

Correct Answer
● an utterance

This answer is correct.

Utterances are used to train and test a Language Understanding app
model. Entities and intents are core components of a Language
Understanding app model, but they are not used for testing the model.
Entity Linking is part of the entity recognition service, which returns links
to external websites to disambiguate terms (entities) identified in a text.
Exercise - Explore language understanding - Training | Microsoft Learn

_________________________

Question
Which tool provides the easiest way to create a knowledge base for Azure
AI Bot Service?

Correct Answer
● the Azure AI Language Studio

This answer is correct.

The Azure AI Language Studio provides the easiest way to create a

knowledge base for Azure Bot Service. While it is possible to create a
knowledge base by using the features of the Machine Learning studio, this
is not the simplest method to accomplish the given objective. The Azure
portal and Azure Cloud Shell allow for creating the Language resource, but
will not create a knowledge base for Azure Bot Service.
Get started with the Language service and Azure Bot Service - Training |
Microsoft Learn

_________________________

Question
What are two required services to build a conversational artificial
intelligence (AI) solution in Azure? Each correct answer presents part of
the solution.

Correct Answer
● Azure AI Bot service

This answer is correct.

●
● Azure AI Language
This answer is correct.

The Azure AI Language service enables you to create a knowledge base of

question-and-answer pairs that can be phrased by users in multiple ways
with the same semantic meaning. A knowledge base is a required data
source to enable the creation of a conversational AI solution. Azure AI Bot
Service provides an interface through which users can interact with the
knowledge base by using one or more channels. Sentiment analysis,
speech synthesis, and Azure AI Content Moderator are not required
features.
Introduction to Bot Framework Composer | Microsoft Learn
Build a bot with the Language Service and Azure Bot Service - Training |
Microsoft Learn

_________________________

Question
Which bot communication channel requires an application to be registered
with the channel?

Correct Answer
● Facebook

This answer is correct.

For a bot to use the Facebook channel, it requires a Facebook application

to be registered. The registered Azure bot can then securely communicate
with users via the Facebook application credentials. Email, Teams, and
web chat do not require a registered application for the channel.
Configure an Azure Bot Service bot to run on one or more channels - Bot
Service | Microsoft Learn
Build a bot with the Language Service and Azure Bot Service - Training |
Microsoft Learn

_________________________

Question
Which natural language processing (NLP) technique normalizes words
before counting them?
Select only one answer.

stemming
This answer is correct.

Stemming normalizes words before counting them. Frequency analysis

counts how often a word appears in a text. N-grams extend frequency
analysis to include multi-term phrases. Vectorization captures semantic
relationships between words by assigning them to locations in n-
dimensional space.
Introduction - Training | Microsoft Learn

_________________________

Question
Which Azure AI Service for Language feature allows you to analyze written
articles to extract information and concepts, such as people and
locations, for classification purposes?
Select only one answer.

named entity recognition

This answer is correct.

Named entity recognition can identify and categorize entities in

unstructured text, such as people, places, organizations, and quantities,
and is suitable to support the development of an article recommendation
system. Key phrase extraction, Content Moderator, and the PII feature are
not suited to entity recognition tasks to build a recommender system.
What is the Named Entity Recognition (NER) feature in Azure Cognitive
Service for Language? – Azure Cognitive Services | Microsoft Learn
Analyze text with the Language service – Training | Microsoft Learn

_________________________

Question
For which two scenarios is the Universal Language Model used by the
speech-to-text API optimized? Each correct answer presents a complete
solution.
Select all answers that apply.

conversational
This answer is correct.

dictation
This answer is correct.

The Universal Language Model used by the speech-to-text API is

optimized for conversational and dictation scenarios. The acoustic,
language, and pronunciation scenarios require developing your own
model.
Get started with speech on Azure - Training | Microsoft Learn
_________________________

Question
Which type of translation does the Azure AI Translator service support?
Select only one answer.

text-to-text
This answer is correct.

The Azure AI Translator service supports text-to-text translation, but it

does not support speech-to-text, text-to-speech, or speech-to-speech
translation.
Get started with translation in Azure - Training | Microsoft Learn

_________________________

Question
Which Azure resource provides direct access to both Azure AI Translator
and Azure AI Speech services through a single endpoint and
authentication key?
Select only one answer.

Azure AI Services
This answer is correct.

Azure AI Services provides direct access to both Azure AI Translator and

Azure AI Speech services through a single endpoint and authentication
key. Azure AI Language service can be used to access the Azure AI
Language service, but not the Azure AI Translator and Azure AI Speech
services. The Machine Learning service is used to design, implement, and
deploy Machine Learning models. Azure AI Bot Service provides a
framework for developing, publishing, and managing bots in Azure.
Get started with translation in Azure - Training | Microsoft Learn

_________________________

Question
When using the Azure AI Service for Language, what should you use to
provide further information online about entities extracted from a text?
Select only one answer.

entity linking
This answer is correct.

Entity Linking identifies and disambiguates the identity of entities found in

a text. Key phrase extraction is not used to extract entities and is used
instead to extract key phrases to identify the main concepts in a text.
Named entity recognition cannot provide a link for each entity to view
further information. Text translation is part of the Azure AI Translator
service.
What is entity linking in Azure Cognitive Service for Language? - Azure
Cognitive Services | Microsoft Learn
Analyze text with the Language service - Training | Microsoft Learn

_________________________

Question
What are the two main schema components of a Language Understanding
app model? Each correct answer presents part of the solution.
Select all answers that apply.

entities
This answer is correct.

intents
This answer is correct.

The two main schema components of a Language Understanding app

model are entities and intents. Utterances play an important role in
training the model, but they are not part of its schema. Entity Linking is
part of the entity recognition service, which returns links to external
websites to disambiguate terms (entities) identified in a text.
Exercise - Explore language understanding - Training | Microsoft Learn

_________________________

Question
What are two main components of a conversational artificial intelligence
(AI) solution? Each correct answer presents part of the solution.
Select all answers that apply.

a bot service
This answer is correct.
 a knowledge base
This answer is correct.

The two main components of a conversational AI solution are a bot service

and a knowledge base. Entity Linking is part of the entity recognition
service, which returns links to external websites to disambiguate terms
(entities) identified in a text. Key phrase extraction evaluates the text of a
document and identifies its main talking points, but it is not one of two
main components of a conversational AI solution.
Introduction - Training | Microsoft Learn

_________________________

Question
Which tool provides the easiest way to create a knowledge base for Azure
AI Bot Service?
Select only one answer.

the Azure AI Language Studio

This answer is correct.

The Azure AI Language Studio provides the easiest way to create a

knowledge base for Azure Bot Service. While it is possible to create a
knowledge base by using the features of the Machine Learning studio, this
is not the simplest method to accomplish the given objective. The Azure
portal and Azure Cloud Shell allow for creating the Language resource, but
will not create a knowledge base for Azure Bot Service.
Get started with the Language service and Azure Bot Service - Training |
Microsoft Learn

_________________________

Question
Which type of machine learning algorithm finds the optimal way to split a
dataset into groups without relying on training and validating label
predictions?

● clustering
This answer is correct.

A clustering algorithm is an example of unsupervised learning, which

groups data points that have similar characteristics without relying on
training and validating label predictions. Supervised learning is a category
of learning algorithms that includes regression and classification, but not
clustering. Classification and regression algorithms are examples of
supervised machine learning.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn
What are classification models? - Training | Microsoft Learn
What is clustering? - Training | Microsoft Learn

_________________________

Question
Which three sources can be used to generate questions and answers for a
knowledge base? Each correct answer presents a complete solution.
Select all answers that apply.

a webpage
This answer is correct.
an existing FAQ document
This answer is correct.
manually entered data
This answer is correct.

A webpage or an existing document, such as a text file containing

question and answer pairs, can be used to generate a knowledge base.
You can also manually enter the knowledge base question-and-answer
pairs. You cannot directly use an image or an audio file to import a
knowledge base.
Build a bot with the Language Service and Azure Bot Service - Training |
Microsoft Learn

_________________________

Question
You need to identify numerical values that represent the probability of
humans developing diabetes based on age and body fat percentage.
Which type of machine learning model should you use?
Select only one answer.

multiple linear regression

This answer is correct.
Multiple linear regression models a relationship between two or more
features and a single label, which matches the scenario in this item. Linear
regression uses a single feature. Logistic regression is a type of
classification model, which returns either a Boolean value or a categorical
decision. Hierarchical clustering groups data points that have similar
characteristics.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn
What are classification models? - Training | Microsoft Learn

_________________________

Question
Predicting rainfall for a specific geographical location is an example of
which type of machine learning?
Select only one answer.

regression
This answer is correct.

Predicting rainfall is an example of regression machine learning, as it will

predict a numeric value for future rainfall by using historical time-series
rainfall data based on factors, such as seasons. Clustering is a machine
learning type that analyzes unlabeled data to find similarities in the data.
Featurization is not a machine learning type, but a collection of
techniques, such as feature engineering, data-scaling, and normalization.
Classification is used to predict categories of data.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
A healthcare organization has a dataset consisting of bone fracture scans
that are categorized by using predefined fracture types. The organization
wants to use machine learning to detect the different types of bone
fractures for new scans before the scans are sent to a medical
practitioner.
Which type of machine learning is this?
Select only one answer.

classification
This answer is correct.

Classification is used to predict categories of data. It can predict which

category or class an item of data belongs to. In this example, a machine
learning model trained by using classification with labeled data can be
used to determine the type of bone fracture in a new scan that is not
labeled already. Featurization is not a machine learning type. Regression is
used to predict numeric values. Clustering analyzes unlabeled data to find
similarities in the data.
Create a classification model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
A retailer wants to group together online shoppers that have similar
attributes to enable its marketing team to create targeted marketing
campaigns for new product launches.
Which type of machine learning is this?
Select only one answer.

clustering
This answer is correct.

Clustering is a machine learning type that analyzes unlabeled data to find

similarities present in the data. It then groups (clusters) similar data
together. In this example, the company can group online customers based
on attributes that include demographic data and shopping behaviors. The
company can then recommend new products to those groups of
customers who are most likely to be interested in them. Classification and
multiclass classification are used to predict categories of data. Regression
is a machine learning scenario that is used to predict numeric values.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
In a regression machine learning algorithm, how are features and labels
handled in a validation dataset?
Select only one answer.
 Features are used to generate predictions for the label, which is
compared to the actual label values.
This answer is correct.

In a regression machine learning algorithm, features are used to generate

predictions for the label, which is compared to the actual label value.
There is no direct comparison of features or labels between the validation
and training datasets.
What is regression? - Training | Microsoft Learn

_________________________

Question
A company is using machine learning to predict house prices based on
appropriate house attributes.
For the machine learning model, which attribute is the label?
Select only one answer.

price of the house

This answer is correct

The price of the house is the label you are attempting to predict through
the machine learning model. This is typically done by using a regression
model. Floor space size, number of bedrooms, and age of the house are
all input variables for the model to help predict the house price label.
What is machine learning? - Training | Microsoft Learn

_________________________

Question
What should you do after preparing a dataset and before training the
machine learning model?
Select only one answer.

split data into training and validation datasets

This answer is correct.

Splitting data into training and validation datasets leaves you with two
datasets, the first and largest of which is the training dataset you use to
train the model. The second, smaller dataset is the held back data and is
called the validation dataset, as it is used to evaluate the trained model. If
normalizing or summarizing the data is required, it will be carried out as
part of data transformation. Cleaning missing data is part of preparing the
data and the data transformation processes.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
You need to create an automated machine learning (automated ML)
model.
Which resource should you create first in Azure Machine Learning studio?
Select only one answer.

a dataset
This answer is correct.

A dataset is required to create an automated machine learning (automated

ML) run. A workspace must be created before you can access Machine
Learning studio. An Azure container instance and an AKS cluster can be
created as a deployment target, after training of a model is complete.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn

_________________________

Question
Which artificial intelligence (AI) technique should be used to extract the
name of a store from a photograph displaying the store front?
Select only one answer.

optical character recognition (OCR)

This answer is correct.

OCR provides the ability to detect and read text in images. NLP is an area
of AI that deals with identifying the meaning of a written or spoken
language, but not detecting or reading text in images. Image classification
classifies images based on their contents. Semantic segmentation
provides the ability to classify individual pixels in an image.
Understand computer vision - Training | Microsoft Learn

_________________________
Question
Which computer vision solution provides the ability to identify a person's
age based on a photograph?
Select only one answer.

facial detection
This answer is correct.

Facial detection provides the ability to detect and analyze human faces in
an image, including identifying a person's age based on a photograph.
Image classification classifies images based on their contents. Object
detection provides the ability to generate bounding boxes identifying the
locations of different types of vehicles in an image. Semantic
segmentation provides the ability to classify individual pixels in an image.
Get started with image analysis on Azure - Training | Microsoft Learn
Understand computer vision - Training | Microsoft Learn

_________________________

Question
Which process allows you to use optical character recognition (OCR)?
Select only one answer.

digitizing medical records

This answer is correct.

OCR can extract printed or handwritten text from images. In this case, it
can be used to extract text from scanned medical records to produce a
digital archive from paper-based documents. Identifying wildlife in an
image is an example of a computer vision solution that uses object
detection and is not suitable for OCR. Identifying a user requesting access
to a laptop is done by taking images from the laptop’s webcam and using
facial detection and recognition to identify the user requesting access.
Translating speech to text is an example of using speech translation and
uses the Azure AI Speech service as part of Azure AI Services.
Read text with the Computer Vision service - Training | Microsoft Learn

_________________________

Question
What allows you to identify different types of bone fractures in X-ray
images?
Select only one answer.

image classification
This answer is correct.

Image classification is part of computer vision and can be used to

evaluate images from an X-ray machine to quickly classify specific bone
fracture types. This helps improve diagnosis and treatment plans. An
image classification model is trained to facilitate the categorizing of the
bone fractures. Object detection is used to return identified objects in an
image, such as a cat, person, or chair. Conversational AI is used to create
intelligent bots that can interact with people by using natural language.
Facial detection is used to detect the location of human faces in an image.
Classify images with the Custom Vision service - Training | Microsoft
Learn

_________________________

Question
Which feature of computer vision involves associating an image with
metadata that summarizes the attributes of the image?
Select only one answer.

tagging
This answer is correct.

Tagging involves associating an image with metadata that summarizes the

attributes of the image. Detecting image types involves identifying clip art
images or line drawings. Content organization involves identifying people
or objects in photos and organizing them based on the identification.
Categorizing involves associating the contents of an image with a limited
set of categories.
Get started with image analysis on Azure - Training | Microsoft Learn

_________________________

Question
Which analytical task of the Azure AI Vision service returns bounding box
coordinates?
Select only one answer.

object detection
This answer is correct.

Detecting objects identifies common objects and, for each, returns

bounding box coordinates. Image categorization assigns a category to an
image, but it does not return bounding box coordinates. Tagging involves
associating an image with metadata that summarizes the attributes of the
image, but it does not return bounding box coordinates. OCR detects
printed and handwritten text in images, but it does not return bounding
box coordinates.
Get started with image analysis on Azure - Training | Microsoft Learn

_________________________

Question
Which additional piece of information is included with each phrase
returned by an image description task of the Azure AI Vision?
Select only one answer.

confidence score
This answer is correct.

Each phrase returned by an image description task of the Azure AI Vision

includes the confidence score. An endpoint and a key must be provided to
access the Azure AI Vision service. Bounding box coordinates are returned
by services such as object detection, but not image description.
Get started with image analysis on Azure - Training | Microsoft Learn

_________________________

Question
Which two Azure AI Document Intelligence models include identifying
common data fields as part of its data extraction capabilities? Each
correct answer presents a complete solution.
Select all answers that apply.

business card model

This answer is correct.

invoice model
This answer is correct.

The business card model analyzes and extracts key information from
business card images and includes common data field extractions, such
as name and email. The invoice model extracts key information from sales
invoices and includes common data fields used in invoices for extraction.
The read model, layout model, and general document model do not
identify and extract common data fields.
Document processing models - Form Recognizer - Azure Applied AI
Services | Microsoft Learn
Analyze receipts with the Form Recognizer service - Training | Microsoft
Learn

_________________________

Question
Which type of artificial intelligence (AI) workload relies on sensors to
proactively detect an impending failure of electronic equipment?
Select only one answer.

anomaly detection
This answer is correct.

Anomaly detection analyzes data collected over time to identify errors or

unusual changes. This allows for predicting impending failures. Other
answer choices represent AI capabilities unrelated to the detecting
impending failures.
Introduction to AI - Training | Microsoft Learn
Understand anomaly detection - Training | Microsoft Learn

_________________________

Question
Which type of artificial intelligence (AI) workload provides the ability to
generate bounding boxes that identify the locations of different types of
vehicles in an image?
Select only one answer.

object detection
This answer is correct.

Object detection provides the ability to generate bounding boxes

identifying the locations of different types of vehicles in an image. The
other answer choices also process images, but their outcomes are
different.
Understand computer vision - Training | Microsoft Learn

_________________________

Question
Which type of artificial intelligence (AI) workload provides the ability to
classify individual pixels in an image depending on the object that they
represent?
Select only one answer.

semantic segmentation
This answer is correct.

Semantic segmentation provides the ability to classify individual pixels in

an image depending on the object that they represent. The other answer
choices also process images, but their outcomes are different.
Understand computer vision - Training | Microsoft Learn

_________________________

Question
Which type of artificial intelligence (AI) workload is used to monitor credit
card transactions?
Select only one answer.

Azure AI Anomaly Detector

This answer is correct.

Azure AI Anomaly Detector analyzes data collected over time to identify

errors or unexpected changes. This allows for identifying unusual credit
card transactions that might indicate a criminal activity. Azure AI
Document Intelligence and image analysis are part of computer vision, so
they do not play any role in credit card transaction processing. Azure AI
Bot Service is part of natural language processing (NLP), without any
significant role in credit card transaction processing.
Understand anomaly detection - Training | Microsoft Learn

_________________________

Question
Which type of artificial intelligence (AI) workload has the primary purpose
of making large amounts of data searchable?
Select only one answer.

knowledge mining
This answer is correct.

Knowledge mining is an artificial intelligence (AI) workload that has the

purpose of making large amounts of data searchable. While other
workloads leverage indexing for faster access to large amounts of data,
this is not their primary purpose.
Understand knowledge mining - Training | Microsoft Learn

_________________________

Question
Which principle of responsible artificial intelligence (AI) defines the
framework of governance and organization principles that meet ethical
and legal standards of AI solutions?
Select only one answer.

accountability
This answer is correct.

Accountability defines the framework of governance and organizational

principles, which are meant to ensure that AI solutions meet ethical and
legal standards that are clearly defined. The other answer choices do not
define the framework of governance and organization principles, but
provide guidance regarding the ethical and legal aspects of the
corresponding standards.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
A bank is developing a new artificial intelligence (AI) system to support
the process of accepting or rejecting mortgage applications.
Which two issues should be considered as part of the responsible AI
principle of fairness to avoid biased decision making? Each correct answer
presents part of the solution.
Select all answers that apply.

ethnicity
This answer is correct.
 gender
This answer is correct.

The AI system must be designed to ensure that biased decision making is

avoided and not based on factors such as ethnicity and gender. The
system will consider salary, payment history, and credit utilization. These
are standard metrics.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
Which principle of responsible artificial intelligence (AI) ensures that an AI
system meets any legal and ethical standards it must abide by?
Select only one answer.

accountability
This answer is correct.

The accountability principle ensures that AI systems are designed to meet

any ethical and legal standards that are applicable. The privacy and
security principle states that AI systems must be designed to protect any
personal and/or sensitive data. The inclusiveness principle states that AI
systems must empower people in a positive and engaging way. The
fairness principle is applied to AI system to ensure that users of the
systems are treated fairly.
Microsoft Azure AI Fundamentals: Explore computer vision - Training |
Microsoft Learn
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
For which scenario should you use anomaly detection?
Select only one answer.

detecting credit card fraud

This answer is correct.

Detecting credit card fraud is an anomaly detection workload that uses

the Azure AI Anomaly Detector service to detect abnormalities in time-
series data. For example, it can compare previous bank transactions to
new transactions and detect abnormalities, such as an unusually large
credit card purchase.
Microsoft Azure AI Fundamentals: Explore computer vision - Training |
Microsoft Learn

_________________________

Question
Which principle of responsible artificial intelligence (AI) involves
evaluating and mitigating the bias introduced by the features of a model?
Select only one answer.

fairness
This answer is correct.

Fairness involves evaluating and mitigating the bias introduced by the

features of a model. Privacy is meant to ensure that privacy provisions are
included in AI solutions. Transparency provides clarity regarding the
purpose of AI solutions, the way they work, as well as their limitations.
Accountability is focused on ensuring that AI solutions meet ethical and
legal standards that are clearly defined.
Understand Responsible AI - Training | Microsoft Learn

_________________________

Question
Which type of machine learning algorithm assigns items to a set of
predefined categories?
Select only one answer.

classification
This answer is correct.

Classification algorithms are used to predict a predefined category to

which an input value belongs. Regression algorithms are used to predict
numeric values. Clustering algorithms group data points that have similar
characteristics. Unsupervised learning is a category of learning algorithms
that includes clustering, but not regression or classification.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn
What are classification models? - Training | Microsoft Learn
What is clustering? - Training | Microsoft Learn
_________________________

Question
A company deploys an online marketing campaign to social media
platforms for a new product launch. The company wants to use machine
learning to measure the sentiment of users on the Twitter platform who
made posts in response to the campaign.
Which type of machine learning is this?
Select only one answer.

classification
This answer is correct.

Classification is used to predict categories of data. It can predict which

category or class an item of data belongs to. In this example, sentiment
analysis can be carried out on the Twitter posts with a numeric value
applied to the posts to identify and classify positive or negative sentiment.
Clustering is a machine learning type that analyzes unlabeled data to find
similarities in the data. Regression is a machine learning scenario that is
used to predict numeric values. Data transformation is not a machine
learning type.
Create a classification model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
What is the purpose of a validation dataset used for as part of the
development of a machine learning model?
Select only one answer.

evaluating the trained model

This answer is correct.

The validation dataset is a sample of data held back from a training

dataset. It is then used to evaluate the performance of the trained model.
Cleaning missing data is used to detect missing values and perform
operations to fix the data or create new values. Feature engineering is part
of preparing the dataset and related data transformation processes.
Summarizing the data is used to provide summary statistics, such as the
mean or count of distinct values in a column.
Create a regression model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
What is an unsupervised machine learning algorithm module for training
models in the Azure Machine Learning designer?
Select only one answer.

K-Means Clustering
This answer is correct.

K-means clustering is an unsupervised machine learning algorithm

component used for training clustering models. You can use unlabeled
data with this algorithm. Linear regression and classification are
supervised machine learning algorithm components. You need labeled
data to use these algorithms. Normalize Data is not a machine learning
algorithm module.
Create a clustering model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
Which part of speech synthesis in natural language processing (NLP)
involves breaking text into individual words such that each word can be
assigned phonetic sounds?
Select only one answer.

tokenization
This answer is correct.

Tokenization is part of speech synthesis that involves breaking text into

individual words such that each word can be assigned phonetic sounds.
Transcribing is part of speech recognition, which involves converting
speech into a text representation. Key phrase extraction is part of
language processing, not speech synthesis. Lemmatization, also known as
stemming, is part of language processing, not speech synthesis.
Recognize and synthesize speech - Training | Microsoft Learn

_________________________

Question
Which three values are returned by the language detection feature of the
Azure AI Language service in Azure?
Select all answers that apply.

ISO 6391 Code

This answer is correct.

Language Name
This answer is correct.

Score
This answer is correct.

Language Name, ISO 6391 Code, and Score are three values returned by
the Language service of natural language processing (NLP) in Azure.
Bounding box coordinates are returned by the Azure AI Vision services in
Azure. Wikipedia URL is one of potential values returned by entity linking
of entity recognition.
Get started with text analysis - Training | Microsoft Learn

_________________________

Question
Which two types of files can be imported to generate a knowledge base
for use with Azure AI Bot Service? Each correct answer presents a
complete solution.
Select all answers that apply.

DOC
This answer is correct.

PDF
This answer is correct.

Structure and unstructured DOC files and PDF files can be imported to
generate a knowledge base for use with Azure AI Bot Service. ZIP files
must first be extracted before they can be imported. MP4 files and CSV
files are not supported to generate question-and-answer pairs for use
with Azure AI Bot Service.
Build a bot with the Language Service and Azure Bot Service - Training |
Microsoft Learn

_________________________
Question
Which two capabilities are supported natively by Azure AI Bot Service?
Each correct answer presents a complete solution.
Select all answers that apply.

responding to email questions

This answer is correct.

responding to new student FAQs

This answer is correct.

A bot can be used to respond to new student queries or to respond to

questions via communication channels, such as email. Azure Bot Service
does not have the capability to translate text. The detection of anomalies
in financial transactions is a workload suited to the Anomaly Detector
service. The classification of image vehicle types is a computer vision
workload and is not suited to a web chatbot.
Build a bot with the Language Service and Azure Bot Service - Training |
Microsoft Learn

_________________________

Question
Which artificial intelligence (AI) technique serves as the foundation for
modern image classification solutions?
Select only one answer.

deep learning
This answer is correct.

Modern image classification solutions are based on deep learning

techniques. Anomaly detection analyzes data collected over time to
identify errors or unusual changes. Both linear regression and multiple
linear regression use training and validating predictions to predict numeric
values, so they are not part of image classification solutions.
Understand classification - Training | Microsoft Learn

_________________________

Question
When using the Face Detect API of the Azure AI Face service, which
feature helps identify whether a human face has glasses or headwear?
Select only one answer.

face attributes
This answer is correct.

Face attributes are a set of features that can be detected by the Face
Detect API. Attributes such as accessories (glasses, mask, headwear etc.)
can be detected. Face rectangle, face ID, and face landmarks do not allow
you to determine whether a person is wearing glasses or headwear.
What is the Azure Face service? - Azure Cognitive Services | Microsoft
Learn
Detect and analyze faces with the Face service - Training | Microsoft
Learn

_________________________

Question
Which service can you use to train an image classification model?
Select only one answer.

Azure AI Custom Vision

This answer is correct.

Azure AI Custom Vision is an image recognition service that allows you to

build and deploy your own image models. The Azure AI vision service,
Azure AI Face service, and Azure AI Language service do not provide the
capability to train your own image model.
What is Custom Vision? - Azure Cognitive Services | Microsoft Learn
Introduction - Training | Microsoft Learn

_________________________

Question
Which type machine learning algorithm predicts a numeric label
associated with an item based on that item’s features?
Select only one answer.

regression
This answer is correct.

The regression algorithms are used to predict numeric values. Clustering

algorithms groups data points that have similar characteristics.
Classification algorithms are used to predict the category to which an
input value belongs. Unsupervised learning is a category of learning
algorithms that includes clustering, but not regression or classification.
Use Automated Machine Learning in Azure Machine Learning - Training |
Microsoft Learn
What are classification models? - Training | Microsoft Learn
What is clustering? - Training | Microsoft Learn

_________________________

Question
You plan to use machine learning to predict the probability of humans
developing diabetes based on their age and body fat percentage.
What should the model include?
Select only one answer.

two features and one label

This answer is correct.

The scenario represents a model that is meant to establish a relationship

between two features (age and body fat percentage) and one label (the
likelihood of developing diabetes). The features are descriptive attributes
(serving as the input), while the label is the characteristic you are trying to
predict (serving as the output).
Multiple linear regression and R-squared - Training | Microsoft Learn

_________________________

Question
Which three data transformation modules are in the Azure Machine
Learning designer? Each correct answer presents a complete solution.
Select all answers that apply.

Clean Missing Data

This answer is correct.

Normalize Data
This answer is correct.

Select Columns in Dataset

This answer is correct.

Normalize Data is a data transformation module that is used to change the

values of numeric columns in a dataset to a common scale, without
distorting differences in the range of values. The Clean Missing Data
module is part of preparing the data and data transformation process.
Select Columns in Dataset is a data transformation component that is
used to choose a subset of columns of interest from a dataset. The train
clustering model is not a part of data transformation. The evaluate model
is a component used to measure the accuracy of training models.
Create a clustering model with Azure Machine Learning designer -
Training | Microsoft Learn

_________________________

Question
You are exploring solutions to improve the document search and indexing
service for employees.
You need an artificial intelligence (AI) search solution that will include
searching text in various types of documents, such as images.
Which type of AI workload is this?
Select only one answer.

data mining
This answer is correct.

Data mining workloads primarily focus on the searching and indexing of

data. The computer vision can be used to extract information from
images, but it is not a search and indexing solution. Conversational AI is
part of natural language processing (NLP) and facilitates the creation of
chatbots. Anomaly detection is not used for searching and indexing data.
This is used to detect outliers in data, such as unusual credit card activity
for the detection of fraud.
Microsoft Azure AI Fundamentals: Explore knowledge mining - Training |
Microsoft Learn

_________________________

Question
Which two artificial intelligence (AI) workload features are part of the
Azure AI Vision service? Each correct answer presents a complete
solution.
Select all answers that apply.

optical character recognition (OCR)

This answer is correct.
spatial analysis
This answer is correct.

OCR and Spatial Analysis are part of the Azure AI Vision service.
Sentiment analysis, entity recognition, and key phrase extraction are not
part of the computer vision service.
Microsoft Azure AI Fundamentals: Explore computer vision – Training |
Microsoft Learn

________________
1. You plan to use Azure AI Document Intelligence's prebuilt receipt
model. Which kind of Azure resource should you create?

Azure AI Document Intelligence or Azure AI services resource.

Correct: Both the Azure AI Document Intelligence resource and the
Azure AI services resource provide access to Azure AI Document
Intelligence.

2. You are using the Azure AI Document Intelligence service to

analyze receipts. Which field types does the service recognize?

Merchant name and address.

Correct: The merchant name and address can be identified using the
receipt model.

3. What is required to use the receipt analyzer service in Azure AI

Document Intelligence?

Create an Azure AI Document Intelligence resource.

Correct: The receipt analyzer model is available as a service when
you create an Azure AI Document Intelligence resource.

________________
1. Which data format is accepted by Azure Cognitive Search when
you're pushing data to the index?

JSON.
Correct. Cognitive Search can index JSON documents. JSON is also
used to define index schemas, indexers, and data source objects.

2. Which explanation best describes an indexer and an index?

An indexer converts documents into JSON and forwards them to a search

engine for indexing.
Correct. An indexer serializes a source document into JSON before
passing it to a search engine for indexing. An indexer automates
several steps of data ingestion, reducing the amount of code you
need to write.

3. If you set up a search index without including a skillset, which

would you still be able to query?

Text content.
Correct. Cognitive Search is used for full text search over indexes
containing alphanumeric content.

________________
1. Computer vision is based on the manipulation and analysis of what
kinds of values in an image?

Pixels
Correct. Pixels are numeric values that represent shade intensity for
points in the image.

2. You want to use the Azure AI Vision service to analyze images. You
also want to use the Azure AI Language service to analyze text. You
want developers to require only one key and endpoint to access all of
your services. What kind of resource should you create in your Azure
subscription?

Azure AI services
Correct. An Azure AI Services resource supports both Azure AI Vision
and Azure AI Language.

3. You want to use the Azure AI Vision service to identify the location
of individual items in an image. Which of the following features
should you retrieve?

Objects
Correct. Azure AI Vision returns objects with a bounding box to
indicate their location in the image.

________________
1. How does the Face service indicate the location of faces in images?

A set of coordinates for each face, defining a rectangular bounding box

around the face
Correct: The locations of detected faces are indicated by coordinates
for a rectangular bounding box

2. What is one aspect that might impair facial detection?

Extreme angles
Correct: Best results are obtained when the faces are full-frontal or
as near as possible to full-frontal

3. What two actions are required to try out the capabilities of the Face
service?

Create a Face resource, and open Vision Studio

Correct: The Face resource has face detections capabilities, and can
be used in Vision Studio to understand its capabilities.

________________
1. You want to extract text from images and then use Azure AI
Language to analyze the text. You want developers to require only
one key and endpoint to access all of your services. What kind of
resource should you create in your Azure subscription?

Azure AI services
Correct. An Azure AI services resource supports both Azure AI Vision
for text extraction, and Azure AI Language for text analytics.
2. You plan to use Azure AI Vision's Read API. What results can the
Read API provide?

Results arranged in pages, lines, and words

Correct: The Read API takes an image and extracts the words,
organizing the results by page and line.

________________
1. You want to use Azure AI Language to determine the key talking
points in a text document. Which feature of the service should you
use?

Key phrase extraction

Correct. Key phrases can be used to identify the main talking points
in a text document.

2. You use Azure AI Language to perform sentiment analysis on a

sentence. The confidence scores .04 positive, .36 neutral, and .60
negative are returned. What do these confidence scores indicate
about the sentence sentiment?

The document is negative.

Correct. The sentiment is most likely the type with the highest
confidence score, in this case .6 negative.

3. When might you see NaN returned for a score in language

detection?

When the language is ambiguous

Correct. The service will return NaN when it can't determine the
language in the provided text.

________________
1. Your organization has an existing frequently asked questions (FAQ)
document. You need to create a knowledge base that includes the
questions and answers from the FAQ with the least possible effort.
What should you do?
Import the existing FAQ document into a new knowledge base.
Correct. You can import question and answer pairs from an existing
FAQ document into a question answering knowledge base.

2. You want to create a knowledge base for your organization’s bot

service. Which Azure AI service is best suited to creating a
knowledge base?

Question Answering
Correct. Question Answering is part of the Azure AI Language service
and enables you to create a knowledge base of question and answer
pairs

________________
1. You need to provision an Azure resource that will be used
to author a new conversational language understanding application.
What kind of resource should you create?

Azure AI Language
Correct. To author a conversational language understanding model,
you need an Azure AI Language resource.

2. You are authoring a conversational language understanding

application to support an international clock. You want users to be
able to ask for the current time in a specified city, for example "What
is the time in London?". What should you do?

Define a "city" entity and a "GetTime" intent with utterances that indicate
the city entity.
Correct. The intent encapsulates the task (getting the time) and the
entity specifies the item to which the intent is applied (the city).

3. You have published your conversational language understanding

application. What information does a client application developer
need to get predictions from it?

The endpoint and key for the application's prediction resource

Correct. Client applications must connect to the endpoint of the
prediction resource, specifying an associated authentication key.

________________
1. You plan to build an application that uses Azure AI Speech to
transcribe audio recordings of phone calls into text, and then submit
the transcribed text to Azure AI Language to extract key phrases. You
want to manage access and billing for the application services with a
single Azure resource. Which type of Azure resource should you
create?

Azure AI services
Correct. This resource would support both the Azure AI Speech and
Azure AI Language services.

2. You want to use Azure AI Speech service to build an application

that reads incoming email message subjects aloud. Which API should
you use?

Text to speech
Correct. The Text to speech API converts text to audible speech.