Tag: AI-900 Practice Exam

AI-900, Microsoft Certification

AI-900: Practice Exam 1 (60 questions with answer key)

Practice Exam 1 – 60 Questions (with Answer key at the end)

Note: The exam is separated into topic sections to help with context and preparation, but the real exam will not be like that.

SECTION 1: Describe Artificial Intelligence workloads and considerations (Questions 1–10)

Question 1 (Single choice)

Which scenario is the best example of an AI workload?

A. A rules-based system that routes emails based on keywords
B. A dashboard that displays historical sales data
C. A system that predicts customer churn based on historical behavior
D. A script that automatically renames files

Question 2 (Multi-select – Choose TWO)

Which characteristics are commonly associated with AI solutions?

A. Deterministic outputs
B. Ability to improve with experience
C. Dependence on labeled or unlabeled data
D. Use of static business rules

Question 3 (Scenario – Single choice)

A company wants to automatically approve or reject loan applications based on past decisions and applicant attributes.
Which AI workload type does this represent?

A. Computer vision
B. Anomaly detection
C. Classification
D. Natural language processing

Question 4 (Matching)

Match each AI workload to its correct description:

AI WorkloadDescription
1. ClassificationA. Identify unusual patterns
2. RegressionB. Assign items to categories
3. ClusteringC. Group similar items without labels
4. Anomaly detectionD. Predict numeric values

Question 5 (Single choice)

Which factor is most important when evaluating the ethical impact of an AI solution?

A. Processing speed
B. Model size
C. Potential bias in training data
D. Storage cost

Question 6 (Scenario – Single choice)

An AI system used for hiring consistently favors one demographic group.
Which Responsible AI principle is most directly violated?

A. Reliability
B. Transparency
C. Fairness
D. Privacy

Question 7 (Multi-select – Choose TWO)

Which scenarios would typically require human oversight when deploying AI solutions?

A. Medical diagnosis recommendations
B. Image resizing
C. Credit approval decisions
D. Log file compression

Question 8 (Fill in the blank)

The ability for users to understand how an AI model makes decisions relates to the principle of __________.

Question 9 (Single choice)

Which workload is best suited for predicting future sales revenue?

A. Classification
B. Regression
C. Clustering
D. Object detection

Question 10 (Scenario – Single choice)

A system groups customers into segments without predefined labels.
Which AI approach is being used?

A. Supervised learning
B. Reinforcement learning
C. Unsupervised learning
D. Deep learning

SECTION 2: Describe fundamental principles of machine learning on Azure (Questions 11–20)

Question 11 (Single choice)

Which Azure service is primarily used to build, train, and deploy machine learning models?

A. Azure AI Vision
B. Azure Machine Learning
C. Azure OpenAI
D. Azure Cognitive Search

Question 12 (Multi-select – Choose TWO)

Which elements are required to train a supervised machine learning model?

A. Labeled data
B. Feature engineering
C. Pretrained transformers
D. Inference endpoints

Question 13 (Scenario – Single choice)

You want to predict house prices based on size, location, and age.
Which type of machine learning model should you use?

A. Classification
B. Regression
C. Clustering
D. Anomaly detection

Question 14 (Single choice)

Which term describes input variables used by a machine learning model?

A. Labels
B. Features
C. Targets
D. Metrics

Question 15 (Matching)

Match the learning type to the description:

Learning TypeDescription
1. SupervisedA. Learns from rewards
2. UnsupervisedB. Uses labeled data
3. ReinforcementC. Finds patterns without labels

Question 16 (Scenario – Multi-select – Choose TWO)

Which actions help reduce overfitting?

A. Increasing model complexity
B. Using more training data
C. Applying regularization
D. Training for more epochs indefinitely

Question 17 (Single choice)

Which metric is most appropriate for evaluating a classification model?

A. Mean Absolute Error
B. R-squared
C. Accuracy
D. RMSE

Question 18 (Fill in the blank)

Splitting data into training and testing sets helps evaluate a model’s __________.

Question 19 (Scenario – Single choice)

You want to visually design and deploy ML models without writing code.
Which Azure feature should you use?

A. Azure ML SDK
B. Azure ML designer
C. Azure OpenAI Studio
D. Azure AI Foundry

Question 20 (Single choice)

Which phase of the ML lifecycle involves using the model to make predictions?

A. Training
B. Validation
C. Inference
D. Feature selection

SECTION 3: Describe features of computer vision workloads on Azure (Questions 21–30)

Question 21 (Single choice)

Which Azure service is used for analyzing images and extracting visual information?

A. Azure AI Language
B. Azure AI Vision
C. Azure Machine Learning
D. Azure Cognitive Search

Question 22 (Scenario – Single choice)

A retail company wants to detect products on shelves using images.
Which computer vision task is required?

A. Image classification
B. OCR
C. Object detection
D. Face recognition

Question 23 (Multi-select – Choose TWO)

Which tasks are supported by Azure AI Vision?

A. Optical character recognition
B. Sentiment analysis
C. Image tagging
D. Language translation

Question 24 (Single choice)

What does OCR stand for?

A. Optical Code Recognition
B. Optical Character Recognition
C. Object Classification Rule
D. Optical Content Rendering

Question 25 (Scenario – Single choice)

You want to extract printed text from scanned invoices.
Which feature should you use?

A. Face detection
B. OCR
C. Image segmentation
D. Video analysis

Question 26 (Matching)

Match the vision task to the outcome:

TaskOutcome
1. Image classificationA. Identify objects and locations
2. Object detectionB. Convert images to text
3. OCRC. Assign labels to images

Question 27 (Single choice)

Which scenario is least appropriate for computer vision?

A. Identifying damaged products
B. Reading license plates
C. Detecting spoken commands
D. Counting people in a room

Question 28 (Scenario – Multi-select – Choose TWO)

Which Responsible AI concerns apply to facial recognition systems?

A. Privacy
B. Bias
C. Latency
D. Overfitting

Question 29 (Single choice)

Which Azure tool provides prebuilt vision models via REST APIs?

A. Azure ML Studio
B. Azure AI Vision
C. Azure OpenAI
D. Azure Data Factory

Question 30 (Fill in the blank)

Detecting the location and boundaries of objects in an image is called __________.

SECTION 4: Describe features of NLP workloads on Azure (Questions 31–40)

Question 31 (Single choice)

Which Azure service is primarily used for NLP workloads?

A. Azure AI Vision
B. Azure AI Language
C. Azure Machine Learning
D. Azure OpenAI

Question 32 (Scenario – Single choice)

You want to identify whether customer reviews are positive or negative.
Which NLP task should you use?

A. Key phrase extraction
B. Named entity recognition
C. Sentiment analysis
D. Language detection

Question 33 (Multi-select – Choose TWO)

Which tasks are supported by Azure AI Language?

A. Entity recognition
B. Text summarization
C. Image captioning
D. Speech synthesis

Question 34 (Single choice)

What is tokenization in NLP?

A. Converting text to audio
B. Splitting text into smaller units
C. Translating languages
D. Removing punctuation

Question 35 (Scenario – Single choice)

You want to extract company names from contracts.
Which NLP feature should you use?

A. Sentiment analysis
B. Language detection
C. Named entity recognition
D. Speech-to-text

Question 36 (Matching)

Match the NLP task to its purpose:

TaskPurpose
1. Language detectionA. Identify people, places, orgs
2. Entity recognitionB. Determine text language
3. Key phrase extractionC. Extract main ideas

Question 37 (Single choice)

Which service converts spoken language into text?

A. Azure AI Language
B. Azure AI Vision
C. Azure AI Speech
D. Azure OpenAI

Question 38 (Scenario – Multi-select – Choose TWO)

Which scenarios use NLP?

A. Chatbots
B. Image classification
C. Document analysis
D. Face detection

Question 39 (Fill in the blank)

Automatically identifying the language of a document is called __________ detection.

Question 40 (Single choice)

Which Azure service combines speech-to-text and text-to-speech capabilities?

A. Azure AI Language
B. Azure AI Vision
C. Azure AI Speech
D. Azure Cognitive Search

SECTION 5: Describe features of generative AI workloads on Azure (Questions 41–60)

Question 41 (Single choice)

What is the defining characteristic of generative AI?

A. Predicting numeric values
B. Generating new content
C. Classifying existing data
D. Detecting anomalies

Question 42 (Scenario – Single choice)

A system generates marketing copy based on a short prompt.
Which model type is being used?

A. Regression model
B. Classification model
C. Large language model
D. Decision tree

Question 43 (Multi-select – Choose TWO)

Which tasks are common for generative AI?

A. Text generation
B. Image generation
C. Anomaly detection
D. Clustering

Question 44 (Single choice)

Which Azure service provides access to GPT models?

A. Azure Machine Learning
B. Azure AI Vision
C. Azure OpenAI
D. Azure AI Language

Question 45 (Scenario – Single choice)

You want to deploy a chat-based AI assistant using Microsoft-managed models.
Which service should you use?

A. Azure ML
B. Azure AI Foundry
C. Azure OpenAI
D. Azure Cognitive Search

Question 46 (Matching)

Match the concept to the description:

ConceptDescription
1. PromptA. Fine-tuning model behavior
2. GroundingB. Input provided to model
3. Fine-tuningC. Connecting to trusted data

Question 47 (Single choice)

What is prompt engineering?

A. Training models from scratch
B. Designing effective model inputs
C. Monitoring model drift
D. Compressing datasets

Question 48 (Scenario – Multi-select – Choose TWO)

Which Responsible AI risks are especially relevant to generative AI?

A. Hallucinations
B. Toxic content
C. Feature scaling
D. Data normalization

Question 49 (Single choice)

Which feature helps ensure generative AI responses are based on company data?

A. Fine-tuning
B. Grounding
C. Tokenization
D. Embedding compression

Question 50 (Fill in the blank)

When a model produces incorrect but confident responses, this is called __________.

Question 51 (Single choice)

Which Azure platform provides a model catalog for generative AI?

A. Azure OpenAI Studio
B. Azure AI Foundry
C. Azure Machine Learning
D. Azure AI Vision

Question 52 (Scenario – Single choice)

You want to compare multiple foundation models before deployment.
Which Azure capability helps most?

A. Azure AI Foundry model catalog
B. Azure ML pipelines
C. Azure Data Factory
D. Azure Synapse

Question 53 (Multi-select – Choose TWO)

Which are considered foundation models?

A. GPT
B. BERT
C. Decision trees
D. Linear regression

Question 54 (Single choice)

Which generative AI workload creates images from text prompts?

A. Text classification
B. Text-to-image generation
C. Image tagging
D. Object detection

Question 55 (Scenario – Single choice)

You want to prevent users from generating harmful content.
Which control is most appropriate?

A. Feature engineering
B. Content filtering
C. Model retraining
D. Data labeling

Question 56 (Matching)

Match the Azure service to its role:

ServiceRole
1. Azure OpenAIA. Custom ML pipelines
2. Azure AI FoundryB. Managed foundation models
3. Azure MLC. Model catalog & orchestration

Question 57 (Single choice)

Which technique reduces hallucinations by connecting models to real data?

A. Fine-tuning
B. Grounding
C. Tokenization
D. Sampling

Question 58 (Scenario – Multi-select – Choose TWO)

Which scenarios are best suited for generative AI?

A. Writing product descriptions
B. Fraud detection
C. Chatbots
D. Forecasting demand

Question 59 (Single choice)

Which principle ensures users know AI-generated content is produced by AI?

A. Fairness
B. Transparency
C. Privacy
D. Reliability

Question 60 (Single choice)

Which Azure tool is commonly used to experiment with prompts?

A. Azure AI Vision Studio
B. Azure OpenAI Studio
C. Azure Data Studio
D. Azure ML designer

Practice Exam 1 – Answer Key

(It is recommended that you review the answers after attempting the exam)

SECTION 1: Describe Artificial Intelligence workloads and considerations (Q1–Q10)

Q1

Correct Answer: C
Explanation:
Predicting customer churn requires learning patterns from historical data, which is a core AI capability.

  • A & D are rule-based automation
  • B is analytics, not AI

Q2

Correct Answers: B, C
Explanation:
AI systems:

  • Improve with experience (learning)
  • Rely on data (labeled or unlabeled)
    They are not deterministic and do not rely purely on static rules.

Q3

Correct Answer: C (Classification)
Explanation:
Approving or rejecting loans is a categorical decision, which makes this a classification problem.

Q4

Correct Matches:

  • 1 → B
  • 2 → D
  • 3 → C
  • 4 → A

Explanation:
These are textbook definitions of AI workload types and frequently tested.

Q5

Correct Answer: C
Explanation:
Bias in training data directly impacts fairness and ethical outcomes. This is a major Responsible AI concern.

Q6

Correct Answer: C (Fairness)
Explanation:
Favoring one demographic group indicates bias, violating the fairness principle.

Q7

Correct Answers: A, C
Explanation:
High-impact decisions (medical, financial) require human oversight.
Low-risk automation does not.

Q8

Correct Answer: Transparency
Explanation:
Transparency means users can understand how and why AI systems make decisions.

Q9

Correct Answer: B (Regression)
Explanation:
Sales revenue is a numeric value, which regression predicts.

Q10

Correct Answer: C (Unsupervised learning)
Explanation:
Grouping data without labels is unsupervised learning.

SECTION 2: Fundamental principles of machine learning on Azure (Q11–Q20)

Q11

Correct Answer: B (Azure Machine Learning)
Explanation:
Azure ML is the primary service for building, training, and deploying ML models.

Q12

Correct Answers: A, B
Explanation:
Supervised learning requires labeled data and feature engineering.
Pretrained models and endpoints are optional.

Q13

Correct Answer: B (Regression)
Explanation:
House prices are numeric → regression.

Q14

Correct Answer: B (Features)
Explanation:
Features are input variables used by the model.

Q15

Correct Matches:

  • 1 → B
  • 2 → C
  • 3 → A

Q16

Correct Answers: B, C
Explanation:
Overfitting is reduced by:

  • More data
  • Regularization
    Increasing complexity worsens overfitting.

Q17

Correct Answer: C (Accuracy)
Explanation:
Accuracy is a common metric for classification problems.

Q18

Correct Answer: Generalization
Explanation:
Train/test splits measure how well a model performs on unseen data.

Q19

Correct Answer: B (Azure ML designer)
Explanation:
Azure ML designer is a no-code/low-code visual tool.

Q20

Correct Answer: C (Inference)
Explanation:
Inference is when the model makes predictions using new data.

SECTION 3: Computer Vision workloads on Azure (Q21–Q30)

Q21

Correct Answer: B (Azure AI Vision)

Q22

Correct Answer: C (Object detection)
Explanation:
Detecting products and their locations requires object detection.

Q23

Correct Answers: A, C
Explanation:
OCR and image tagging are vision tasks.
Sentiment and translation are NLP.

Q24

Correct Answer: B (Optical Character Recognition)

Q25

Correct Answer: B (OCR)

Q26

Correct Matches:

  • 1 → C
  • 2 → A
  • 3 → B

Q27

Correct Answer: C
Explanation:
Spoken commands are a speech workload, not vision.

Q28

Correct Answers: A, B
Explanation:
Facial recognition raises privacy and bias concerns.

Q29

Correct Answer: B (Azure AI Vision)

Q30

Correct Answer: Object detection

SECTION 4: NLP workloads on Azure (Q31–Q40)

Q31

Correct Answer: B (Azure AI Language)

Q32

Correct Answer: C (Sentiment analysis)

Q33

Correct Answers: A, B

Q34

Correct Answer: B
Explanation:
Tokenization splits text into words or subwords.

Q35

Correct Answer: C (Named entity recognition)

Q36

Correct Matches:

  • 1 → B
  • 2 → A
  • 3 → C

Q37

Correct Answer: C (Azure AI Speech)

Q38

Correct Answers: A, C

Q39

Correct Answer: Language

Q40

Correct Answer: C (Azure AI Speech)

SECTION 5: Generative AI workloads on Azure (Q41–Q60)

Q41

Correct Answer: B
Explanation:
Generative AI creates new content.

Q42

Correct Answer: C (Large language model)

Q43

Correct Answers: A, B

Q44

Correct Answer: C (Azure OpenAI)

Q45

Correct Answer: C (Azure OpenAI)

Q46

Correct Matches:

  • 1 → B
  • 2 → C
  • 3 → A

Q47

Correct Answer: B
Explanation:
Prompt engineering is crafting effective inputs.

Q48

Correct Answers: A, B

Q49

Correct Answer: B (Grounding)

Q50

Correct Answer: Hallucinations

Q51

Correct Answer: B (Azure AI Foundry)

Q52

Correct Answer: A

Q53

Correct Answers: A, B

Q54

Correct Answer: B

Q55

Correct Answer: B (Content filtering)

Q56

Correct Matches:

  • 1 → B
  • 2 → C
  • 3 → A

Q57

Correct Answer: B (Grounding)

Q58

Correct Answers: A, C

Q59

Correct Answer: B (Transparency)

Q60

Correct Answer: B (Azure OpenAI Studio)

Go to the AI-900 Exam Prep Hub main page.

AI-900, Microsoft Certification

AI-900: Practice Exam 2 (60 questions with answers)

Below are 60 questions. The questions are broken up into topic sections to help with context and preparation. The real exam is not like that.

Section 1: Describe Artificial Intelligence workloads and considerations (Q1–Q10)

Q1. A city wants to automatically adjust traffic light timing based on real‑time vehicle congestion detected from sensors. Which type of AI workload is MOST appropriate?

  • A. Classification
  • B. Anomaly detection
  • C. Prediction and optimization
  • D. Computer vision

Q2. (Multi‑select) Which characteristics distinguish AI solutions from traditional software? (Choose two.)

  • A. Deterministic logic paths
  • B. Ability to learn from data
  • C. Adaptation over time
  • D. Manual rule updates only

Q3. An application analyzes medical images to identify whether a tumor is benign or malignant. Which AI workload is this?

  • A. Regression
  • B. Clustering
  • C. Classification
  • D. Forecasting

Q4. (Matching) Match the Responsible AI principle to its description.

PrincipleDescription
1. Reliability & SafetyA. Protects personal and sensitive data
2. Privacy & SecurityB. Ensures consistent and dependable performance
3. TransparencyC. Explains how decisions are made

Q5. Why is explainability especially important in AI systems used for healthcare decisions?

  • A. It improves system performance
  • B. It reduces infrastructure costs
  • C. It builds trust and supports accountability
  • D. It eliminates the need for human oversight

Q6. An AI model performs well in testing but fails frequently in real‑world use. Which Responsible AI principle is MOST impacted?

  • A. Fairness
  • B. Transparency
  • C. Reliability & safety
  • D. Inclusiveness

Q7. (Multi‑select) Which scenarios require human‑in‑the‑loop decision making? (Choose two.)

  • A. Automated photo tagging
  • B. Credit approval systems
  • C. Medical diagnosis support
  • D. Spam email filtering

Q8. Fill in the blank: An AI system that ensures users understand why a specific output was generated is demonstrating __________.

Q9. A retailer predicts next month’s total revenue using historical sales data. What AI workload does this represent?

  • A. Classification
  • B. Regression
  • C. Clustering
  • D. Anomaly detection

Q10. Which concern arises when an AI system unintentionally favors one demographic group over others?

  • A. Reliability
  • B. Bias
  • C. Security
  • D. Performance

Section 2: Describe fundamental principles of machine learning on Azure (Q11–Q20)

Q11. Which Azure service is designed to build, train, and deploy machine learning models at scale?

  • A. Azure AI Vision
  • B. Azure Machine Learning
  • C. Azure OpenAI
  • D. Azure AI Language

Q12. (Multi‑select) Which components are required for supervised learning? (Choose two.)

  • A. Labeled data
  • B. Features
  • C. Unlabeled datasets
  • D. Prompt templates

Q13. A model predicts the number of support tickets expected per day. Which ML task is this?

  • A. Classification
  • B. Regression
  • C. Clustering
  • D. Ranking

Q14. In machine learning, what is a feature?

  • A. The predicted output
  • B. An input variable
  • C. A training algorithm
  • D. A deployment endpoint

Q15. (Matching) Match the learning type to the scenario.

Learning TypeScenario
1. SupervisedA. Grouping customers by behavior
2. UnsupervisedB. Predicting house prices
3. ReinforcementC. Training a robot using rewards

Q16. Which problem occurs when a model memorizes training data but performs poorly on new data?

  • A. Underfitting
  • B. Overfitting
  • C. Bias
  • D. Drift

Q17. Which metric is MOST commonly used to evaluate classification models?

  • A. RMSE
  • B. Accuracy
  • C. MAE
  • D. R²

Q18. Why is data split into training and test sets?

  • A. To reduce storage requirements
  • B. To improve inference speed
  • C. To evaluate generalization
  • D. To eliminate bias

Q19. Which Azure ML capability allows building models without writing code?

  • A. Jupyter notebooks
  • B. Azure ML designer
  • C. REST endpoints
  • D. Pipelines

Q20. Fill in the blank: Using a trained model to make predictions on new data is called __________.

Section 3: Describe features of computer vision workloads on Azure (Q21–Q30)

Q21. Which Azure service provides image analysis, OCR, and object detection?

  • A. Azure AI Language
  • B. Azure AI Vision
  • C. Azure AI Speech
  • D. Azure Machine Learning

Q22. A solution identifies people and vehicles in security footage and draws bounding boxes around them. What vision capability is required?

  • A. Image classification
  • B. Face recognition
  • C. Object detection
  • D. OCR

Q23. (Multi‑select) Which tasks are computer vision workloads? (Choose two.)

  • A. Image tagging
  • B. Sentiment analysis
  • C. OCR
  • D. Language translation

Q24. Extracting printed text from scanned invoices is an example of:

  • A. Object detection
  • B. OCR
  • C. Image segmentation
  • D. Face analysis

Q25. Which capability identifies the emotional attributes of a face in an image?

  • A. OCR
  • B. Face analysis
  • C. Image classification
  • D. Object detection

Q26. (Matching) Match the vision task to the description.

TaskDescription
1. Image classificationA. Detects text in images
2. OCRB. Assigns a label to an entire image
3. Object detectionC. Locates objects with bounding boxes

Q27. Which scenario is NOT a computer vision workload?

  • A. Counting people in a store
  • B. Detecting defects in products
  • C. Converting speech to text
  • D. Reading license plates

Q28. (Multi‑select) What are common concerns with facial recognition systems? (Choose two.)

  • A. Privacy
  • B. Bias
  • C. Cost optimization
  • D. Network latency

Q29. Which Azure service supports OCR for handwritten text?

  • A. Azure Machine Learning
  • B. Azure AI Vision
  • C. Azure OpenAI
  • D. Azure AI Speech

Q30. Fill in the blank: Identifying the location and category of multiple objects in an image is called __________.

Section 4: Describe features of NLP workloads on Azure (Q31–Q40)

Q31. Which Azure service provides sentiment analysis, entity recognition, and key phrase extraction?

  • A. Azure AI Vision
  • B. Azure AI Language
  • C. Azure OpenAI
  • D. Azure AI Speech

Q32. An application determines whether customer feedback is positive, negative, or neutral. What NLP task is this?

  • A. Translation
  • B. Entity recognition
  • C. Sentiment analysis
  • D. Language modeling

Q33. (Multi‑select) Which tasks fall under NLP workloads? (Choose two.)

  • A. Key phrase extraction
  • B. Named entity recognition
  • C. Image tagging
  • D. Object detection

Q34. What is tokenization in NLP?

  • A. Translating text
  • B. Breaking text into smaller units
  • C. Assigning sentiment scores
  • D. Detecting entities

Q35. Identifying names of people, places, and organizations in text is known as:

  • A. Translation
  • B. Sentiment analysis
  • C. Entity recognition
  • D. Language detection

Q36. (Matching) Match the NLP task to the scenario.

TaskScenario
1. TranslationA. Detects emotional tone
2. Sentiment analysisB. Converts text between languages
3. Key phrase extractionC. Summarizes main topics

Q37. Which Azure service converts spoken language into text?

  • A. Azure AI Vision
  • B. Azure AI Language
  • C. Azure AI Speech
  • D. Azure OpenAI

Q38. (Multi‑select) Which use cases are appropriate for speech synthesis? (Choose two.)

  • A. Voice assistants
  • B. Image labeling
  • C. Accessibility tools
  • D. Object detection

Q39. Fill in the blank: Detecting the language of a document is a __________ task.

Q40. Which Azure service supports both speech‑to‑text and text‑to‑speech?

  • A. Azure AI Vision
  • B. Azure AI Language
  • C. Azure AI Speech
  • D. Azure Machine Learning

Section 5: Describe features of generative AI workloads on Azure (Q41–Q60)

Q41. What distinguishes generative AI from predictive ML?

  • A. It only classifies data
  • B. It creates new content
  • C. It requires no training data
  • D. It cannot use text input

Q42. Large language models are primarily trained on:

  • A. Structured tables only
  • B. Images
  • C. Massive text datasets
  • D. Sensor data

Q43. (Multi‑select) Which are common generative AI use cases? (Choose two.)

  • A. Text summarization
  • B. Image generation
  • C. Fraud detection
  • D. Forecasting

Q44. Which Azure service provides access to GPT‑based models?

  • A. Azure AI Language
  • B. Azure Machine Learning
  • C. Azure OpenAI
  • D. Azure AI Vision

Q45. A chatbot that answers questions using natural language is an example of:

  • A. Computer vision
  • B. Predictive ML
  • C. Generative AI
  • D. Rule‑based automation

Q46. (Matching) Match the concept to its description.

ConceptDescription
1. PromptA. AI‑generated incorrect content
2. HallucinationB. Input provided to a model
3. GroundingC. Using trusted data sources

Q47. What is prompt engineering?

  • A. Training new models
  • B. Designing effective inputs
  • C. Deploying endpoints
  • D. Cleaning datasets

Q48. (Multi‑select) Which Responsible AI considerations apply to generative AI? (Choose two.)

  • A. Content safety
  • B. Bias mitigation
  • C. Image resolution
  • D. Compute scaling

Q49. Which technique helps reduce hallucinations by referencing verified information?

  • A. Fine‑tuning
  • B. Grounding
  • C. Tokenization
  • D. Sampling

Q50. Fill in the blank: When a generative AI model produces confident but incorrect outputs, it is known as __________.

Q51. Which Azure platform helps manage, evaluate, and deploy generative AI solutions responsibly?

  • A. Azure Machine Learning
  • B. Azure AI Foundry
  • C. Azure AI Vision
  • D. Azure AI Language

Q52. What capability does the Azure AI Foundry model catalog provide?

  • A. Access to prebuilt and foundation models
  • B. Image labeling
  • C. Speech transcription
  • D. Data storage

Q53. (Multi‑select) Which actions support responsible generative AI deployment? (Choose two.)

  • A. Human review
  • B. Content filtering
  • C. Unlimited model access
  • D. Ignoring bias metrics

Q54 (Scenario-Based | Single Select)

A marketing team wants to generate short product descriptions automatically based on a few bullet points provided by users. The solution should generate natural-sounding text and allow control over tone (for example, professional or casual).

Which AI approach is most appropriate?

A. Image classification
B. Predictive regression modeling
C. Generative AI using a large language model
D. Rule-based text templating

Q55 (Scenario-Based | Multi-Select)

You are designing a generative AI solution using Azure OpenAI Service for internal employees. The solution will generate responses to HR-related questions.

Which Responsible AI considerations should be addressed?
(Select all that apply)

A. Data privacy and protection
B. Model transparency
C. Bias and fairness
D. Object detection accuracy
E. Content safety and filtering

Q56 (Matching)

Match each Azure service or capability to its primary use case.

Azure Service / CapabilityUse Case
1. Azure OpenAI ServiceA. Analyze sentiment in customer feedback
2. Azure AI LanguageB. Generate natural language text from prompts
3. Azure AI VisionC. Detect objects and extract image features
4. Azure AI SpeechD. Convert spoken language into text

Q57 (Scenario-Based | Single Select)

A developer wants to experiment with different foundation models, compare their performance, and select a model to deploy for a generative AI chatbot.

Which Azure capability best supports this requirement?

A. Azure Machine Learning pipelines
B. Azure AI Foundry model catalog
C. Azure AI Vision Studio
D. Azure AI Speech Studio

Q58 (Fill in the Blank)

In a generative AI solution, the text or instructions provided by the user to guide the model’s output is called a __________.

Q59 (Scenario-Based | Multi-Select)

An organization plans to deploy a generative AI application that summarizes internal documents. The documents may contain sensitive employee data.

Which actions help reduce risk?
(Select all that apply)

A. Apply role-based access control (RBAC)
B. Use data encryption at rest and in transit
C. Disable content filtering to improve creativity
D. Limit model access to approved users
E. Log and monitor prompt and response usage

Q60 (Scenario-Based | Single Select)

You are evaluating whether a business problem is best solved using generative AI rather than traditional machine learning.

Which scenario is the best candidate for generative AI?

A. Predicting next month’s sales total
B. Classifying emails as spam or not spam
C. Generating a draft response to a customer support request
D. Detecting fraudulent credit card transactions

Practice Exam 2 – Answer Key

(It is recommended that you review the answers after attempting the exam)

Describe AI Workloads & Considerations (Q1–Q10)

Question 1

Correct Answer: C
Explanation:
AI workloads focus on enabling machines to perceive, learn, reason, and act. Automation alone does not imply AI.

Question 2

Correct Answer: B
Explanation:
Image classification is a computer vision AI workload, not a traditional automation or rules-based system.

Question 3

Correct Answer: A
Explanation:
Fairness ensures AI systems do not introduce or reinforce bias against groups of users.

Question 4

Correct Answers: A, C
Explanation:
Reliability and safety focus on consistency, error handling, and preventing harm. Performance tuning alone is not sufficient.

Question 5

Correct Answer: D
Explanation:
Accountability ensures humans remain responsible for AI decisions and outcomes.

Question 6

Correct Answer: B
Explanation:
Transparency requires that users understand how and why AI systems behave as they do.

Question 7

Correct Answers: A, D
Explanation:
Privacy and security focus on protecting data and controlling access.

Question 8

Correct Answer: C
Explanation:
Inclusiveness ensures AI systems are usable by people of different abilities and backgrounds.

Question 9

Correct Answer: B
Explanation:
AI workloads often require training on large datasets, unlike static rule-based systems.

Question 10

Correct Answer: A
Explanation:
Predictive outcomes based on patterns is a defining feature of AI workloads.

Machine Learning Principles (Q11–Q22)

Question 11

Correct Answer: B
Explanation:
Regression predicts continuous numeric values, such as sales or temperature.

Question 12

Correct Answer: A
Explanation:
Classification predicts discrete labels (spam vs. not spam).

Question 13

Correct Answer: C
Explanation:
Clustering groups unlabeled data based on similarity.

Question 14

Correct Answer: D
Explanation:
Features are input variables; labels are the outcomes the model learns to predict.

Question 15

Correct Answer: B
Explanation:
Training data teaches the model; validation data evaluates performance.

Question 16

Correct Answer: A
Explanation:
Automated ML automatically selects algorithms and tunes hyperparameters.

Question 17

Correct Answer: C
Explanation:
Azure Machine Learning provides compute, data management, and model lifecycle tools.

Question 18

Correct Answer: B
Explanation:
Model deployment makes trained models available as web services or endpoints.

Question 19

Correct Answer: D
Explanation:
Deep learning uses multi-layer neural networks to learn complex patterns.

Question 20

Correct Answer: A
Explanation:
Transformers use attention mechanisms to process sequences efficiently.

Question 21

Correct Answer: B
Explanation:
Validation datasets help detect overfitting.

Question 22

Correct Answer: C
Explanation:
Azure ML supports versioning, monitoring, and retraining.

Computer Vision Workloads (Q23–Q32)

Question 23

Correct Answer: A
Explanation:
Image classification assigns labels to images.

Question 24

Correct Answer: B
Explanation:
Object detection identifies objects and their locations.

Question 25

Correct Answer: C
Explanation:
OCR extracts printed or handwritten text from images.

Question 26

Correct Answer: D
Explanation:
Facial detection identifies faces; analysis can infer attributes.

Question 27

Correct Answer: A
Explanation:
Azure AI Vision provides image analysis, OCR, and object detection.

Question 28

Correct Answer: B
Explanation:
Face detection identifies faces without identifying individuals.

Question 29

Correct Answer: C
Explanation:
OCR is ideal for digitizing scanned documents.

Question 30

Correct Answer: D
Explanation:
Computer vision solutions analyze visual content.

Question 31

Correct Answer: A
Explanation:
Bounding boxes are used in object detection.

Question 32

Correct Answer: B
Explanation:
Vision Studio allows testing models without writing code.

NLP Workloads (Q33–Q43)

Question 33

Correct Answer: C
Explanation:
Key phrase extraction identifies important terms in text.

Question 34

Correct Answer: A
Explanation:
Entity recognition identifies names, locations, organizations, etc.

Question 35

Correct Answer: B
Explanation:
Sentiment analysis determines emotional tone.

Question 36

Correct Answer: D
Explanation:
Language models predict the next token in a sequence.

Question 37

Correct Answer: A
Explanation:
Speech recognition converts spoken language into text.

Question 38

Correct Answer: C
Explanation:
Text-to-speech generates spoken output from text.

Question 39

Correct Answer: B
Explanation:
Translation converts text between languages.

Question 40

Correct Answer: A
Explanation:
Azure AI Language provides NLP capabilities.

Question 41

Correct Answer: C
Explanation:
Azure AI Speech handles speech-to-text and text-to-speech.

Question 42

Correct Answer: D
Explanation:
NLP workloads process and analyze human language.

Question 43

Correct Answer: B
Explanation:
Tokenization breaks text into smaller units.

Generative AI Workloads (Q44–Q60)

Question 44

Correct Answer: C
Explanation:
Generative AI creates new content rather than predicting labels.

Question 45

Correct Answer: A
Explanation:
Large Language Models are trained on massive text datasets.

Question 46

Correct Answer: B
Explanation:
Azure OpenAI provides access to generative models.

Question 47

Correct Answer: D
Explanation:
Prompt engineering shapes model output.

Question 48

Correct Answer: A
Explanation:
Generative AI is ideal for summarization and content creation.

Question 49

Correct Answer: C
Explanation:
Responsible AI mitigates hallucinations and bias.

Question 50

Correct Answer: B
Explanation:
Content filtering prevents unsafe outputs.

Question 51

Correct Answer: A
Explanation:
Azure AI Foundry centralizes model experimentation and deployment.

Question 52

Correct Answer: D
Explanation:
Model catalogs allow model discovery and comparison.

Question 53

Correct Answer: B
Explanation:
Generative AI is best for open-ended responses.

Question 54

Correct Answer: C
Explanation:
LLMs generate natural language with tone control.

Question 55

Correct Answers: A, B, C, E
Explanation:
Privacy, fairness, transparency, and content safety are critical.

Question 56

Correct Matches:
1 → B
2 → A
3 → C
4 → D

Question 57

Correct Answer: B
Explanation:
Azure AI Foundry model catalog supports model comparison.

Question 58

Correct Answer: Prompt
Explanation:
Prompts guide model behavior.

Question 59

Correct Answers: A, B, D, E
Explanation:
Security controls and monitoring reduce risk.

Question 60

Correct Answer: C
Explanation:
Generative AI excels at creating human-like text responses.

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