200 Practice Questions For Azure AI-
900 Fundamentals Exam Questions
with Correct Answers
What are NLP services in Microsoft Azure? - Answer-Text AnalyticsUse this service
to analyze text documents and extract key phrases, detect entities (such as places,
dates, and people), and evaluate sentiment (how positive or negative a document
is).Translator TextUse this service to translate text between more than 60
languages.SpeechUse this service to recognize and synthesize speech, and to
translate spoken languages.Language Understanding Intelligent Service (LUIS)Use
this service to train a language model that can understand spoken or text-based
commands.
What are the Conversational AI services in Microsoft Azure? - Answer-QnA
MakerThis cognitive service enables you to quickly build a knowledge base of
questions and answers that can form the basis of a dialog between a human and an
AI agent.Azure Bot ServiceThis service provides a platform for creating, publishing,
and managing bots. Developers can use the Bot Framework to create a bot and
manage it with Azure Bot Service - integrating back-end services like QnA Maker
and LUIS, and connecting to channels for web chat, email, Microsoft Teams, and
others.
What is responsible AI? - Answer-Artificial Intelligence is a powerful tool that can be
used to greatly benefit the world. However, like any tool, it must be used
responsibly.At Microsoft, AI software development is guided by a set of six
principles, designed to ensure that AI applications provide amazing solutions to
difficult problems without any unintended negative consequences.
What are the six guiding principles of responsible AI? - Answer-Fairness: AI systems
should treat all people fairly. For example, suppose you create a machine learning
model to support a loan approval application for a bank. The model should make
predictions of whether or not the loan should be approved without incorporating any
bias based on gender, ethnicity, or other factors that might result in an unfair
advantage or disadvantage to specific groups of applicants.
Reliability and safety: AI systems should perform reliably and safely. For example,
consider an AI-based software system for an autonomous vehicle; or a machine
learning model that diagnoses patient symptoms and recommends prescriptions.
Unreliability in these kinds of system can result in substantial risk to human life.
Privacy and security: AI systems should be secure and respect privacy. The machine
learning models on which AI systems are based rely on large volumes of data, which
may contain personal details that must be kept private. Even after the models are
trained and the system is in production, it uses new data to make predictions or take
action that may be subject to privacy or security concerns.
,Inclusiveness: AI systems should empower everyone and engage people. AI should
bring benefits to all parts of society, regardless of physical ability, gender, sexual
orientation, ethnicity, or other factors.
Transparency: AI systems should be understandable. Users should be made fully
aware of the purpose of the system, how it works, and what limitations may be
expected.
Accountability: People should be accountable for AI systems. Designers and
developers of AI-based solution should work within a framework of governance and
organizational principles that ensure the solution meets ethical and legal standards
that are clearly defined.
You want to create a model to predict sales of ice cream based on historic data that
includes daily ice cream sales totals and weather measurements. Which Azure
service should you use? - Answer-Azure Machine Learning
You want to train a model that classifies images of dogs and cats based on a
collection of your own digital photographs. Which Azure service should you use? -
Answer-Computer Vision
You are designing an AI application that uses computer vision to detect cracks in car
windshields, and warns drivers when a windshield should be repaired or replaced.
When tested in good lighting conditions, the application successfully detects 99% of
dangerously damaged glass. Which of the following statements should you include in
the application's user interface? - Answer-When used in good lighting conditions, this
application can be used to identify potentially dangerous cracks and defects in
windshields. If you suspect your windshield is damaged, even if the application does
not detect any defects, you should have it inspected by a professional.
You create a machine learning model to support a loan approval application for a
bank. The model should make predictions of whether or not the loan should be
approved without incorporating any bias based on gender, ethnicity, or other factors
that might result in an unfair advantage or disadvantage to specific groups of
applicants. Which principle of responsible AI does this come under? - Answer-
Fairness
AI-based software application development must be subjected to rigorous testing
and deployment management processes to ensure that they work as expected
before release. Which principle of responsible AI does this come under? - Answer-
Reliability and safety
The machine learning models on which AI systems are based rely on large volumes
of data, which may contain personal details that must be kept private. Which
principle of responsible AI does this come under? - Answer-Privacy and security
AI systems should empower everyone and engage people. AI should bring benefits
to all parts of society, regardless of physical ability, gender, sexual orientation,
ethnicity, or other factors. Which principle of responsible AI does this come under? -
Answer-Inclusiveness
, I systems should be understandable. Users should be made fully aware of the
purpose of the system, how it works, and what limitations may be expected. Which
principle of responsible AI does this come under? - Answer-Transparency
Designers and developers of AI-based solutions should work within a framework of
governance and organizational principles that ensure the solution meets ethical and
legal standards that are clearly defined. Which principle of responsible AI does this
come under? - Answer-Accountability
Adventure Works Cycles is a business that rents cycles in a city. The business could
use historic data to train a model that predicts daily rental demand in order to make
sure sufficient staff and cycles are available. Which service should you use? -
Answer-Azure Machine Learning
What are the various kinds of machine learning models? - Answer-Regression
(supervised machine learning)We use historic data to trian the model to predict the
numerical value
Classification (supervised machine learning)We can fit the features into the model
and predict the classification of the label
Unsupervised Machine learningYou don't have a label to predict. you only have
features. You have to create clusters based on the features.
What is the process of machine learning regardless of the model? - Answer-Data
IgestionYou need to get the data to train your modelData
Pre processingIdentify the features that helps the model to predict and discarding
others
Data CleaningFix any erros or remving the items which has erros
Replacing Feature Valuesfind the replacement feature values if any missing. In this
process you might use exisiting feature engineering to find the value
Apply AlgoritmsApply alogorithms on this data for the processing until you are happy
with the model pridictions
Deploy ModelFianlly you deploy your model into machine learning service so that
applications can connect to it.
To use Azure Machine Learning, you create a workspace in your Azure subscription.
Is this true? - Answer-TrueYou can then use this workspace to manage data,
compute resources, code, models, and other artifacts related to your machine
learning workloads.
What is the benefit of using the Azure Machine learning service? - Answer-Data
scientists expend a lot of effort exploring and pre-processing data, and trying various
types of model-training algorithm to produce accurate models, which is time
900 Fundamentals Exam Questions
with Correct Answers
What are NLP services in Microsoft Azure? - Answer-Text AnalyticsUse this service
to analyze text documents and extract key phrases, detect entities (such as places,
dates, and people), and evaluate sentiment (how positive or negative a document
is).Translator TextUse this service to translate text between more than 60
languages.SpeechUse this service to recognize and synthesize speech, and to
translate spoken languages.Language Understanding Intelligent Service (LUIS)Use
this service to train a language model that can understand spoken or text-based
commands.
What are the Conversational AI services in Microsoft Azure? - Answer-QnA
MakerThis cognitive service enables you to quickly build a knowledge base of
questions and answers that can form the basis of a dialog between a human and an
AI agent.Azure Bot ServiceThis service provides a platform for creating, publishing,
and managing bots. Developers can use the Bot Framework to create a bot and
manage it with Azure Bot Service - integrating back-end services like QnA Maker
and LUIS, and connecting to channels for web chat, email, Microsoft Teams, and
others.
What is responsible AI? - Answer-Artificial Intelligence is a powerful tool that can be
used to greatly benefit the world. However, like any tool, it must be used
responsibly.At Microsoft, AI software development is guided by a set of six
principles, designed to ensure that AI applications provide amazing solutions to
difficult problems without any unintended negative consequences.
What are the six guiding principles of responsible AI? - Answer-Fairness: AI systems
should treat all people fairly. For example, suppose you create a machine learning
model to support a loan approval application for a bank. The model should make
predictions of whether or not the loan should be approved without incorporating any
bias based on gender, ethnicity, or other factors that might result in an unfair
advantage or disadvantage to specific groups of applicants.
Reliability and safety: AI systems should perform reliably and safely. For example,
consider an AI-based software system for an autonomous vehicle; or a machine
learning model that diagnoses patient symptoms and recommends prescriptions.
Unreliability in these kinds of system can result in substantial risk to human life.
Privacy and security: AI systems should be secure and respect privacy. The machine
learning models on which AI systems are based rely on large volumes of data, which
may contain personal details that must be kept private. Even after the models are
trained and the system is in production, it uses new data to make predictions or take
action that may be subject to privacy or security concerns.
,Inclusiveness: AI systems should empower everyone and engage people. AI should
bring benefits to all parts of society, regardless of physical ability, gender, sexual
orientation, ethnicity, or other factors.
Transparency: AI systems should be understandable. Users should be made fully
aware of the purpose of the system, how it works, and what limitations may be
expected.
Accountability: People should be accountable for AI systems. Designers and
developers of AI-based solution should work within a framework of governance and
organizational principles that ensure the solution meets ethical and legal standards
that are clearly defined.
You want to create a model to predict sales of ice cream based on historic data that
includes daily ice cream sales totals and weather measurements. Which Azure
service should you use? - Answer-Azure Machine Learning
You want to train a model that classifies images of dogs and cats based on a
collection of your own digital photographs. Which Azure service should you use? -
Answer-Computer Vision
You are designing an AI application that uses computer vision to detect cracks in car
windshields, and warns drivers when a windshield should be repaired or replaced.
When tested in good lighting conditions, the application successfully detects 99% of
dangerously damaged glass. Which of the following statements should you include in
the application's user interface? - Answer-When used in good lighting conditions, this
application can be used to identify potentially dangerous cracks and defects in
windshields. If you suspect your windshield is damaged, even if the application does
not detect any defects, you should have it inspected by a professional.
You create a machine learning model to support a loan approval application for a
bank. The model should make predictions of whether or not the loan should be
approved without incorporating any bias based on gender, ethnicity, or other factors
that might result in an unfair advantage or disadvantage to specific groups of
applicants. Which principle of responsible AI does this come under? - Answer-
Fairness
AI-based software application development must be subjected to rigorous testing
and deployment management processes to ensure that they work as expected
before release. Which principle of responsible AI does this come under? - Answer-
Reliability and safety
The machine learning models on which AI systems are based rely on large volumes
of data, which may contain personal details that must be kept private. Which
principle of responsible AI does this come under? - Answer-Privacy and security
AI systems should empower everyone and engage people. AI should bring benefits
to all parts of society, regardless of physical ability, gender, sexual orientation,
ethnicity, or other factors. Which principle of responsible AI does this come under? -
Answer-Inclusiveness
, I systems should be understandable. Users should be made fully aware of the
purpose of the system, how it works, and what limitations may be expected. Which
principle of responsible AI does this come under? - Answer-Transparency
Designers and developers of AI-based solutions should work within a framework of
governance and organizational principles that ensure the solution meets ethical and
legal standards that are clearly defined. Which principle of responsible AI does this
come under? - Answer-Accountability
Adventure Works Cycles is a business that rents cycles in a city. The business could
use historic data to train a model that predicts daily rental demand in order to make
sure sufficient staff and cycles are available. Which service should you use? -
Answer-Azure Machine Learning
What are the various kinds of machine learning models? - Answer-Regression
(supervised machine learning)We use historic data to trian the model to predict the
numerical value
Classification (supervised machine learning)We can fit the features into the model
and predict the classification of the label
Unsupervised Machine learningYou don't have a label to predict. you only have
features. You have to create clusters based on the features.
What is the process of machine learning regardless of the model? - Answer-Data
IgestionYou need to get the data to train your modelData
Pre processingIdentify the features that helps the model to predict and discarding
others
Data CleaningFix any erros or remving the items which has erros
Replacing Feature Valuesfind the replacement feature values if any missing. In this
process you might use exisiting feature engineering to find the value
Apply AlgoritmsApply alogorithms on this data for the processing until you are happy
with the model pridictions
Deploy ModelFianlly you deploy your model into machine learning service so that
applications can connect to it.
To use Azure Machine Learning, you create a workspace in your Azure subscription.
Is this true? - Answer-TrueYou can then use this workspace to manage data,
compute resources, code, models, and other artifacts related to your machine
learning workloads.
What is the benefit of using the Azure Machine learning service? - Answer-Data
scientists expend a lot of effort exploring and pre-processing data, and trying various
types of model-training algorithm to produce accurate models, which is time
