Are you preparing for the Microsoft AI-900 exam? The AI-900 is designed to test your foundational knowledge of artificial intelligence (AI) and machine learning concepts, specifically in the context of Microsoft Azure. With the exam covering topics such as cloud computing, machine learning, and AI workloads, preparing properly is key to ensuring success.
In this blog post, we’ve compiled 50 practice test questions to help you test your knowledge and get one step closer to acing the exam. Whether you’re just getting started or you’re in the final stages of preparation, these practice questions will help you review key concepts and sharpen your skills.
1. What is Artificial Intelligence (AI)?
- a) A system that can solve problems and make decisions based on data.
- b) A network of neurons that mimics the human brain.
- c) A machine that can perform calculations.
- d) A program designed for data storage.
Answer: a) A system that can solve problems and make decisions based on data.
2. Which of the following is NOT a type of AI?
- a) Reactive Machines
- b) Limited Memory
- c) Theory of Mind
- d) Complex Memory
Answer: d) Complex Memory
3. What is the primary purpose of Machine Learning?
- a) To program a machine to perform tasks.
- b) To allow the machine to learn from data and improve its performance over time.
- c) To store large amounts of data for retrieval.
- d) To make machines smarter than humans.
Answer: b) To allow the machine to learn from data and improve its performance over time.
4. Which Azure service allows you to build, train, and deploy machine learning models?
- a) Azure Machine Learning
- b) Azure Cognitive Services
- c) Azure Bot Services
- d) Azure Functions
Answer: a) Azure Machine Learning
5. What is the primary goal of Natural Language Processing (NLP)?
- a) To create neural networks for deep learning.
- b) To allow computers to understand and process human languages.
- c) To automate repetitive tasks.
- d) To improve speech recognition.
Answer: b) To allow computers to understand and process human languages.
6. Which Azure service can be used for anomaly detection in data?
- a) Azure Cognitive Services
- b) Azure Databricks
- c) Azure AI
- d) Azure Anomaly Detector
Answer: d) Azure Anomaly Detector
7. Which type of machine learning model uses labeled data for training?
- a) Unsupervised Learning
- b) Supervised Learning
- c) Reinforcement Learning
- d) Semi-supervised Learning
Answer: b) Supervised Learning
8. What does the Azure AI Bot Services do?
- a) Automates IT support tasks
- b) Allows developers to create, test, and deploy intelligent bots
- c) Provides machine learning models for analysis
- d) Creates data models for business analysis
Answer: b) Allows developers to create, test, and deploy intelligent bots
9. Which Azure service can be used for anomaly detection in data?
- a) Azure Cognitive Services
- b) Azure Databricks
- c) Azure AI
- d) Azure Anomaly Detector
Answer: d) Azure Anomaly Detector
10. Which of the following is an example of supervised learning?
- a) K-means clustering
- b) Decision trees
- c) Self-organizing maps
- d) Reinforcement learning
Answer: b) Decision trees
11. What is the main purpose of the Azure Cognitive Services Text Analytics API?
- a) Text classification
- b) Sentiment analysis
- c) Object recognition
- d) Text-to-speech
Answer: b) Sentiment analysis
12. What does the Azure Face API provide?
- a) Text-to-speech capabilities
- b) Facial recognition and analysis
- c) Speech-to-text translation
- d) Image classification
Answer: b) Facial recognition and analysis
13. Which Azure service helps you to build and deploy predictive models?
- a) Azure Databricks
- b) Azure Machine Learning
- c) Azure Cognitive Services
- d) Azure Functions
Answer: b) Azure Machine Learning
14. What is the primary feature of Azure Databricks?
- a) Text analysis
- b) Machine learning model deployment
- c) Real-time analytics and collaborative data science
- d) Object recognition
Answer: c) Real-time analytics and collaborative data science
15. Which service in Azure allows you to deploy models as APIs for real-time predictions?
- a) Azure Functions
- b) Azure Cognitive Services
- c) Azure Machine Learning
- d) Azure Databricks
Answer: c) Azure Machine Learning
16. What is the purpose of the Azure Custom Vision service?
- a) To analyze text data for sentiment
- b) To identify and classify objects in images
- c) To translate text into multiple languages
- d) To process speech data
Answer: b) To identify and classify objects in images
17. Which Azure service helps with automated language translation?
- a) Azure Cognitive Services
- b) Azure Language Understanding (LUIS)
- c) Azure Translator Text API
- d) Azure Vision API
Answer: c) Azure Translator Text API
18. What is the primary function of Azure’s Language Understanding (LUIS)?
- a) Recognizing emotions in text
- b) Converting text to speech
- c) Analyzing images
- d) Understanding user intentions from natural language
Answer: d) Understanding user intentions from natural language
19. What is the primary benefit of using Azure Cognitive Search?
- a) Automated language translation
- b) Searching through large amounts of text data
- c) Image recognition
- d) Analyzing speech data
Answer: b) Searching through large amounts of text data
20. What kind of data does Azure’s Computer Vision service work with?
- a) Text
- b) Images and videos
- c) Audio and speech
- d) Sensor data
Answer: b) Images and videos
21. Which AI service helps you identify anomalies in time-series data?
- a) Azure Anomaly Detector
- b) Azure Custom Vision
- c) Azure Cognitive Search
- d) Azure Bot Services
Answer: a) Azure Anomaly Detector
22. What is a neural network?
- a) A computer network that can process large data sets
- b) A collection of algorithms designed to mimic the human brain’s operation
- c) A platform for machine learning deployment
- d) A type of database
Answer: b) A collection of algorithms designed to mimic the human brain’s operation
23. What is reinforcement learning?
- a) Learning from labeled data to make predictions
- b) Learning from feedback to maximize a reward
- c) Unsupervised learning with clustering
- d) A type of supervised learning
Answer: b) Learning from feedback to maximize a reward
24. Which of the following is NOT an AI capability provided by Azure Cognitive Services?
- a) Speech recognition
- b) Text analytics
- c) Image recognition
- d) Video compression
Answer: d) Video compression
25. What is the role of Azure’s Speech-to-Text API?
- a) Translates speech into written text
- b) Recognizes objects in video
- c) Converts text to speech
- d) Detects emotions in voice
Answer: a) Translates speech into written text
26. Which machine learning model works best for classification problems?
- a) K-means clustering
- b) Linear regression
- c) Decision trees
- d) Neural networks
Answer: c) Decision trees
27. Which service in Azure helps with building intelligent conversational agents?
- a) Azure Cognitive Services
- b) Azure Bot Services
- c) Azure Machine Learning
- d) Azure Databricks
Answer: b) Azure Bot Services
28. What is the primary difference between supervised and unsupervised learning?
- a) Supervised learning uses labeled data; unsupervised learning uses unlabeled data
- b) Supervised learning is faster than unsupervised learning
- c) Unsupervised learning is more accurate
- d) Supervised learning requires more complex algorithms
Answer: a) Supervised learning uses labeled data; unsupervised learning uses unlabeled data
29. Which of the following best describes machine learning?
- a) Machines that follow instructions exactly
- b) Machines that improve their performance by learning from data
- c) Machines that perform repetitive tasks without learning
- d) Machines that require explicit programming for each task
Answer: b) Machines that improve their performance by learning from data
30. Which Azure service provides a pre-built, customizable object detection model?
- a) Azure Cognitive Services
- b) Azure Custom Vision
- c) Azure Machine Learning
- d) Azure Databricks
Answer: b) Azure Custom Vision
31. Which Azure service is best suited for real-time streaming analytics?
- a) Azure Machine Learning
- b) Azure Databricks
- c) Azure Stream Analytics
- d) Azure Cognitive Services
Answer: c) Azure Stream Analytics
32. What is a decision tree in machine learning?
- a) A type of neural network
- b) A hierarchical model used to make decisions based on data
- c) A clustering technique
- d) A reinforcement learning method
Answer: b) A hierarchical model used to make decisions based on data
33. Which of the following is NOT a feature of Azure Cognitive Services?
- a) Language understanding
- b) Image recognition
- c) Automated machine learning pipeline deployment
- d) Speech-to-text conversion
Answer: c) Automated machine learning pipeline deployment
34. What type of machine learning algorithm is typically used in recommender systems?
- a) Classification
- b) Clustering
- c) Regression
- d) Collaborative filtering
Answer: d) Collaborative filtering
35. What is the difference between regression and classification in machine learning?
- a) Regression predicts continuous values; classification predicts discrete labels
- b) Classification predicts continuous values; regression predicts discrete labels
- c) Regression is more accurate
- d) There is no difference
Answer: a) Regression predicts continuous values; classification predicts discrete labels
36. Which of the following is an example of unsupervised learning?
- a) Decision trees
- b) K-means clustering
- c) Neural networks
- d) Logistic regression
Answer: b) K-means clustering
37. Which of the following Azure services provides capabilities for automatic speech translation?
- a) Azure Cognitive Services
- b) Azure Machine Learning
- c) Azure Translator
- d) Azure Databricks
Answer: c) Azure Translator
38. What is a key challenge in machine learning?
- a) Lack of computational power
- b) Gathering sufficient quality data for training
- c) Writing complex algorithms
- d) Overfitting to test data
Answer: b) Gathering sufficient quality data for training
39. Which of the following best describes the concept of “overfitting” in machine learning?
- a) The model generalizes well to new data
- b) The model fails to recognize patterns in training data
- c) The model is too complex and performs well on training data but poorly on new data
- d) The model is too simple to capture any patterns
Answer: c) The model is too complex and performs well on training data but poorly on new data
40. What is the purpose of Azure Machine Learning Studio?
- a) To visualize data
- b) To develop machine learning models with drag-and-drop tools
- c) To store training data
- d) To deploy machine learning models
Answer: b) To develop machine learning models with drag-and-drop tools
41. Which type of machine learning uses historical data to predict future outcomes?
- a) Unsupervised learning
- b) Supervised learning
- c) Reinforcement learning
- d) Predictive learning
Answer: b) Supervised learning
42. What is the primary function of the Azure Speech SDK?
- a) To analyze speech data
- b) To convert text into speech
- c) To transcribe speech into text
- d) To enhance audio quality
Answer: c) To transcribe speech into text
43. What is a common application of image recognition in Azure Cognitive Services?
- a) Sentiment analysis of text
- b) Object detection in images
- c) Text-to-speech conversion
- d) Translation of languages
Answer: b) Object detection in images
44. Which of the following is NOT a use case for Azure Bot Services?
- a) Customer support automation
- b) Employee training
- c) Automating repetitive tasks
- d) Developing chatbots for social media
Answer: b) Employee training
45. What type of learning involves interaction between an agent and its environment to maximize reward?
- a) Supervised learning
- b) Unsupervised learning
- c) Reinforcement learning
- d) Deep learning
Answer: c) Reinforcement learning
46. What does “training” a machine learning model involve?
- a) Programming the model to solve a task
- b) Feeding the model with labeled data to improve accuracy
- c) Testing the model’s predictions
- d) Deploying the model to production
Answer: b) Feeding the model with labeled data to improve accuracy
47. What is the primary goal of data preprocessing in machine learning?
- a) To reduce the amount of data
- b) To remove irrelevant features from data
- c) To clean and transform data for better model performance
- d) To visualize data
Answer: c) To clean and transform data for better model performance
48. What is a common challenge when using unsupervised learning?
- a) Lack of labeled data
- b) Difficulty in interpreting the results
- c) Limited computational power
- d) Overfitting
Answer: b) Difficulty in interpreting the results
49. What does the “training data” refer to in machine learning?
- a) Data used to test the model
- b) Data used to train the model to make predictions
- c) Data used to evaluate the model’s performance
- d) Data used to validate the model’s accuracy
Answer: b) Data used to train the model to make predictions
50. What type of machine learning is best for grouping similar data points?
- a) Supervised learning
- b) Unsupervised learning
- c) Reinforcement learning
- d) Deep learning
Answer: b) Unsupervised learning
Frequently Asked Questions (FAQ)
1. How do I prepare for the AI-900 exam?
The best way to prepare is by understanding core AI concepts and services in Microsoft Azure. Use resources like the Microsoft Learn platform, study guides, practice tests, and tutorials. Additionally, hands-on experience with Azure AI services will give you a practical understanding.
2. What topics are covered in the AI-900 exam?
The AI-900 exam covers topics like:
- AI fundamentals and principles
- Machine learning concepts
- Azure AI services (e.g., Azure Machine Learning, Cognitive Services)
- Natural Language Processing (NLP)
- Computer Vision and speech recognition
3. How many questions are on the AI-900 exam?
The AI-900 exam typically consists of 40-60 multiple-choice questions. The exact number may vary, and the exam duration is approximately 60 minutes.
4. What is the passing score for the AI-900 exam?
The passing score for the AI-900 exam is 700 out of 1000. It is important to review the exam objectives thoroughly and practice with sample questions to ensure you’re ready.
5. Can I retake the AI-900 exam if I fail?
Yes, if you fail the AI-900 exam, you can retake it. However, there is a 24-hour waiting period before you can retake the exam. If you fail three times, you’ll need to wait 14 days before attempting again.