AI-900 Azure AI Fundamentals Certification Exam Questions

The Microsoft Azure AI Fundamentals certification is an entry-level artificial intelligence certification designed for professionals who want to build foundational knowledge of AI concepts and Microsoft Azure AI services. Commonly associated with the AI-900 exam, this certification validates your understanding of machine learning principles, computer vision, natural language processing ( NLP ), generative AI basics, and conversational AI solutions within the Microsoft Azure ecosystem.

The Azure AI Fundamentals certification is ideal for beginners, students, business professionals, cloud enthusiasts, data analysts, and IT professionals who want to explore artificial intelligence without requiring deep programming expertise. It is also valuable for individuals planning to pursue advanced Microsoft AI certifications or careers in AI engineering, machine learning, cloud computing, automation, and intelligent application development.

This page provides Azure AI Fundamentals certification sample questions, exam preparation guidance, AI-900 exam insights, study strategies, and foundational AI concepts aligned with the latest Microsoft certification objectives. The goal is to help certification aspirants strengthen conceptual understanding and become familiar with the real exam format, question styles, and key Azure AI services frequently tested in the certification exam.

Using practice questions is one of the most effective ways to prepare for the Azure AI Fundamentals certification exam. Practice-based learning helps candidates identify weak areas, improve confidence, understand Microsoft terminology, and become comfortable with scenario-based AI questions. Instead of relying only on theoretical reading, solving realistic AI-900 sample questions allows learners to apply concepts related to machine learning workloads, responsible AI principles, Azure Cognitive Services, computer vision, and generative AI capabilities in practical exam scenarios.

As artificial intelligence adoption continues to grow across industries such as healthcare, finance, retail, cybersecurity, and enterprise automation, the Azure AI Fundamentals certification helps learners build industry-recognized foundational AI knowledge that supports both career growth and future specialization in cloud AI technologies.

Table of Contents

• Microsoft AI 900 Exam Details Table

• How to Prepare Microsoft AI 900 Certification?

• Career Benefits of Microsoft AI 900 Certification

• Exam Tips Of Microsoft AI 900 Certification

• FAQs - Microsoft AI 900 Certification

Azure AI Fundamentals ( AI 900 ) Certification - Exam Details

Exam Detail	Information
Certification	Microsoft Azure AI Fundamentals
Exam Code	AI-900
Provider	Microsoft
Certification Level	Fundamentals / Beginner Level
Exam Focus	Artificial Intelligence & Azure AI Services
Questions	Approximately 40–60 Questions
Exam Duration	60 Minutes
Exam Format	Multiple Choice, Scenario-Based, Drag & Drop
Passing Score	700 / 1000
Exam Delivery	Online Proctored or Authorized Test Center
Exam Cost	Varies by country/region
Recommended Experience	Basic understanding of cloud computing and AI concepts
Key Skills Measured	Machine Learning, NLP, Computer Vision, Generative AI, Responsible AI
Official Exam Language	Multiple Languages Supported
Validity	Microsoft role-based certifications policies apply
Difficulty Level	Beginner to Intermediate
Ideal Candidates	Students, Beginners, AI Enthusiasts, Cloud Professionals, Business Users
Technologies Covered	Azure AI Services, Azure Machine Learning, Cognitive Services, Generative AI Concepts
Career Relevance	AI Fundamentals, Cloud AI, Intelligent Applications, Automation
Popular Job Paths	AI Associate, Cloud Support, Data & AI Beginner Roles, Technical Consultant

The Azure AI Fundamentals (AI-900) certification exam is designed to validate foundational AI knowledge rather than advanced coding expertise. Candidates are expected to understand core AI workloads, responsible AI principles, machine learning fundamentals, and the capabilities of Microsoft Azure AI services. The exam also introduces real-world AI use cases, making it highly valuable for professionals beginning their journey into artificial intelligence and cloud-based AI solutions.

How to Prepare for the Azure AI Fundamentals (AI-900) Certification

Preparing for the Microsoft Azure AI Fundamentals exam requires a balanced approach that combines conceptual understanding, practical exposure to Azure AI services, and consistent practice with exam-style questions. Since this certification is designed for beginners, the primary focus should be on understanding how artificial intelligence solutions are applied in real-world business and cloud environments rather than memorizing complex technical implementations.

Start by building a strong foundation in core AI concepts such as machine learning, computer vision, natural language processing (NLP), conversational AI, and generative AI. Candidates should clearly understand how these technologies work and where they are used within the Microsoft Azure ecosystem. Learning the differences between supervised learning, unsupervised learning, and predictive AI workloads is especially important for the AI-900 exam.

Hands-on practice is highly valuable even for a fundamentals-level certification. Explore Azure AI services such as:

• Azure AI Vision

• Azure AI Language

• Azure AI Speech

• Azure AI Bot Service

• Azure Machine Learning

• Azure OpenAI Service

Practical exposure helps candidates understand service capabilities, use cases, and Microsoft terminology commonly used in exam questions.

Mock exams and practice questions play a critical role in preparation. Regular practice helps improve familiarity with:

• Scenario-based questions

• AI workload identification

• Responsible AI principles

• Azure service selection

• Real exam timing patterns

While practicing, carefully analyze incorrect answers to identify weak areas. Many candidates struggle with differentiating between Azure AI services and understanding which AI solution best fits a business scenario. Creating short notes for commonly confused concepts can significantly improve retention.

Time management is another important preparation strategy. Instead of studying long hours occasionally, maintain a consistent daily study schedule focused on one AI domain at a time. Beginners often benefit from dividing preparation into smaller learning blocks such as:

• AI fundamentals

• Machine learning concepts

• Computer vision

• NLP

• Generative AI

• Responsible AI

Official Microsoft learning paths, documentation, and sandbox environments are among the best preparation resources because they align directly with the latest AI-900 exam objectives. Combining official resources with certification practice questions creates a well-rounded study approach that improves both conceptual clarity and exam confidence.

Reviewed & Verified by CertiMaan Certification Support Team

This Microsoft Azure AI Fundamentals exam questions page has been carefully reviewed by the CertiMaan Certification Support Team to ensure accuracy, relevance, and alignment with the latest Microsoft Azure AI Fundamentals certification objectives. The sample questions, preparation guidance, and AI learning resources provided on this page are designed to help certification aspirants strengthen foundational artificial intelligence knowledge and prepare confidently for the AI-900 certification exam.

Our review process focuses on validating the accuracy of Azure AI concepts, Microsoft AI terminology, cloud-based AI workloads, and exam-relevant learning objectives commonly measured in the certification assessment. The content is continuously evaluated against evolving Azure AI technologies, responsible AI principles, machine learning concepts, and Microsoft Azure AI service updates to maintain high educational quality and certification relevance.

The CertiMaan Certification Support Team analyzes:

• Official Microsoft certification objectives

• Azure AI service capabilities

• AI workload mapping

• Real-world business AI use cases

• Beginner-level AI learning requirements

• Scenario-based certification question patterns

This review methodology helps ensure that learners receive practical, trustworthy, and exam-focused preparation content suitable for both beginners and professionals exploring artificial intelligence within the Microsoft Azure ecosystem.

The practice content on this page is intended to improve conceptual understanding, reinforce AI fundamentals, and help candidates become familiar with the types of AI-related questions commonly encountered in the Azure AI Fundamentals certification exam.

Topics Reviewed

• Artificial Intelligence Fundamentals

• Machine Learning Concepts

• Responsible AI Principles

• Azure AI Services

• Natural Language Processing (NLP)

• Computer Vision

• Conversational AI

• Generative AI Basics

• Azure Machine Learning

• AI Workload Scenarios

Career Benefits of the Microsoft Azure AI Fundamentals

The Azure AI Fundamentals certification provides a strong starting point for professionals who want to enter the rapidly growing field of artificial intelligence and cloud computing. As organizations across industries continue adopting AI-powered solutions for automation, analytics, customer engagement, and intelligent decision-making, foundational AI knowledge has become increasingly valuable for both technical and non-technical professionals.

Earning the Microsoft Azure AI Fundamentals certification demonstrates that you understand essential AI concepts and how AI solutions are implemented using Microsoft Azure technologies. This helps candidates build credibility when applying for entry-level cloud, AI, and technology-focused roles.

One of the biggest advantages of the Azure AI Fundamentals certification is that it creates a pathway toward more advanced Microsoft AI and cloud certifications. Many learners use AI-900 as a stepping stone before pursuing certifications related to:

• Azure AI Engineer

• Azure Data Scientist

• Azure Administrator

• Machine Learning Engineering

• Cloud Solution Architecture

The certification is especially useful for professionals working in:

• IT support

• Cloud operations

• Business analysis

• Software development

• Data analysis

• Digital transformation initiatives

• Automation and intelligent systems

Because the exam focuses on practical AI workloads and real-world business scenarios, candidates gain knowledge that is directly applicable to modern enterprise environments. Understanding concepts such as machine learning, computer vision, natural language processing, and responsible AI helps professionals participate more effectively in AI-driven projects and cloud transformation strategies.

The Azure AI Fundamentals certification also improves professional visibility in a competitive job market. Employers increasingly value candidates who understand AI terminology, cloud AI services, and responsible AI practices, even in non-developer roles. This certification signals that the learner has invested time in understanding emerging technologies shaping the future of business and innovation.

Some common career paths associated with foundational AI knowledge include:

• AI Support Associate

• Junior Cloud Engineer

• AI Project Coordinator

• Technical Consultant

• Data & AI Associate

• Business Technology Analyst

• Cloud Solutions Support Specialist

Beyond career opportunities, the certification helps learners develop confidence in discussing AI technologies, evaluating AI solutions, and understanding how intelligent applications are built within cloud ecosystems. This foundational understanding becomes highly valuable as AI adoption continues expanding across healthcare, finance, retail, manufacturing, cybersecurity, and enterprise software industries.

40+ AI-900 Azure AI Fundamentals Certification Sample Questions List :

1. Extracting key insights from structured and unstructured data sources is a feature of what type of workload?

1. Natural Language Processing

2. Computer Vision

3. Anomaly detection

4. Knowledge Mining

2. Training of a custom image classification model“ can be performed by using the Computer Vision service.

1. No

2. Yes

3. Your team member is planning to use the Form Recognizer pre-built receipt model.Which kind of Azure resource should you recommend to create?

1. Computer Vision

2. Form Recognizer

3. Face Service

4. A banking system, that predicts whether a loan will be repaid or not, is an example of what type of machine learning?Select the correct option.

1. Classification

2. Clustering

3. Regression

5. Identifying suspicious sign-ins by looking for deviations from normal patterns is an example of anomaly detection.

1. Yes

2. No

6. Which type of machine learning should you use to predict the sale price of auctioned items.

1. Regression

2. Clustering

3. Classification

7. A media company is implementing an AI system that entitles everyone including people with disabilities such as vision impairment, deaf or hard of hearing. Identify the Microsoft guiding principle for responsible AI which the company is trying to implement.

1. Inclusiveness

2. Accountability

3. Reliability and safety

4. Fairness

8. An automobile dealership wants to use historic car sales data to train a machine learning model. The model should predict the price of a pre-owned car based on its make, model, engine size, and mileage. What kind of machine learning model should the dealership use automated machine learning to create?

1. Classification

2. Time Series

3. Regression

9. An automated chat to answer questions about refunds and exchange.

1. Knowledge Mining

2. Natural Language Processing

3. Computer vision

4. Anomaly Detection

5. Conversational AI

10. When training a model why should you randomly split the rows into separate subsets?

1. To train multiple models simultaneously to attain better performance

2. To train the model twice to achieve better accuracy

3. To test the model by using data that was not used to train the model

11. Which service has the capability to detect printed and handwritten text in images?

1. Text Analytics

2. Computer Vision- OCR

3. Translator Text

12. Keyphrase extraction can be used to retrieve all city names in a text string.

1. No

2. Yes

13. You have a lecture note which is sorted as text. For your exam, you need to extract key terms from the notes to generate summaries. Which type of AI workload should you use?

1. Anomaly detection

2. Conversational AI

3. Natural language processing

4. Computer vision

14. You are building a Language Understanding model for an e-commerce business. You need to ensure that the model detects when utterances are outside the intended scope of the model. What should you do?

1. Create a prebuilt task entity

2. Create a new model

3. Add utterances to the None intent

4. Test the model by using new utterances

15. A separate chatbot is required for each communication channel.

1. No

2. Yes

16. Select the most appropriate Natural Language Processing workload for below scenario. Scenario: Translate email communication to a specific language.

1. Language modelling

2. Translation

3. Sentiment analysis

4. Speech recognition and speech synthesis

5. Entity recognition

6. Key phrase extraction

17. Smart home devices that answer questions like “What is the weather today?“ are an example of natural language processing.

1. Yes

2. No

18. From the listed scenarios, select correct scenario where Natural language processing can be used

1. Stop a process in a factory when extremely high temperatures are registered.

2. Classify email messages as work-related or personal.

3. Predict the number of future car rentals.

4. Predict which website visitors will make a transaction.

19. Choose an answer and complete the sentence correctly. Identifying segments of your customer base using Recency, Frequency, Monetary (RFM) values ?? is [ ].

1. This is an example of regularization.

2. This is an example of classification.

3. An example of regression.

4. This is an example of clustering.

20. “Answering frequently asked questions“ is a scenario of Conversational AI.

1. No

2. Yes

Exam Tips for Microsoft Azure AI Fundamentals ( AI-900 ) Certification

Preparing for the Microsoft Azure AI Fundamentals exam becomes much easier when candidates understand the exam structure, question patterns, and the types of AI concepts commonly tested by Microsoft. Since the AI-900 certification focuses on foundational artificial intelligence knowledge, success depends more on conceptual clarity and practical understanding than deep technical coding expertise.

One of the most effective exam strategies is to first understand the major exam domains. Candidates should focus heavily on:

• Artificial Intelligence workloads

• Machine Learning fundamentals

• Computer Vision concepts

• Natural Language Processing (NLP)

• Conversational AI

• Responsible AI principles

• Azure AI services and use cases

Many AI-900 questions are scenario-based, where candidates must identify the most suitable Azure AI solution for a business requirement. Instead of memorizing definitions alone, try to understand:

• When a service is used

• Why it is used

• What business problem it solves

• Which AI capability it supports

A common mistake beginners make is confusing Azure AI services with similar functionalities. Spend extra time comparing services such as:

• Azure AI Vision vs Face Detection

• Azure AI Language vs Conversational AI

• Azure Machine Learning vs Prebuilt AI Services

Creating small comparison notes can improve retention and reduce confusion during the exam.

Time management is another important factor. Although the AI-900 exam is beginner-friendly, some questions may contain lengthy business scenarios. Practice reading questions carefully and identifying keywords related to:

• Prediction

• Classification

• Conversational AI

• Sentiment analysis

• Image recognition

• Responsible AI

Mock exams and certification practice questions are extremely valuable because they simulate the real exam experience. Regular practice helps candidates:

• Improve confidence

• Identify weak domains

• Understand Microsoft exam terminology

• Adapt to question structure

• Reduce exam anxiety

When reviewing practice tests, focus more on understanding incorrect answers rather than only tracking scores. This approach improves conceptual understanding and long-term retention.

Another highly recommended strategy is using hands-on Azure learning environments. Even basic exposure to Azure AI services helps learners better understand:

• Service capabilities

• AI workflows

• Real-world implementation scenarios

• Cloud AI terminology

Before the exam day:

• Review key AI concepts

• Avoid last-minute cramming

• Practice time management

• Read each question carefully

• Eliminate obviously incorrect options first

Maintaining a calm and confident mindset is equally important. Since the Azure AI Fundamentals certification is designed for beginners and AI newcomers, candidates who combine consistent study, official learning resources, and regular practice questions typically perform well in the exam.

21. In a group of people,  _______ facial recognition task can able to point out, who the person is.

1. Grouping

2. Verification

3. Similarity

4. Identification

22. You plan to build an application that uses the Speech service to transcribe audio recordings of phone calls into text. You also plan to submit the transcribed text to the Text Analytics service to extract key phrases. Moreover, you want to manage access and billing for the application services in a single Azure resource. Which type of Azure resource should you create?

1. Speech

2. Cognitive Services

3. Text Analytics

4. Custom Vision

23. Web chatbots can interact with users visiting a website.

1. Yes

2. No

24. “Providing an explanation of the outcome of a credit loan application“ is an example of the Microsoft transparency principle for responsible AI.

1. No

2. Yes

25. Which scenario is an example of webchat bot?

1. Translate into English questions entered by customers at a kiosk so that the appropriate person can call the customer

2. Determine whether reviews entered on a website for a concert are positive or negative

3. From a website interface answer common questions about the  scheduled events and ticket purchases for a music festival

4. Accepts questions through email and then route the email messages to the correct person based on the content of the message

26. Pair the facial recognition task with appropriate questions. Whether the two face images are of the same person.

1. Grouping

2. Verification

3. Similarity

4. Identification

27. Automated machine learning is the process of automating time-consuming and repetitive tasks in machine learning model development.

1. No

2. Yes

28. You need to develop a mobile app that allows your employees to scan and save expenses while traveling. What Kind of Computer Vision Should you Use?

1. Object detection

2. Optical Character Recognition (OCR)

3. Image classification

4. Face detection

29. If you create a Cognitive Services resource, client applications need different keys and endpoint for different service they use.

1. Yes

2. No

30. Language services can be used to extract key entities from phone transcripts.

1. No

2. Yes

31. You can detect the location of content in an image by creating an object detection model with the Custom Vision service.

1. Yes

2. No

32. _____ can be used to build no-code apps that use built-in natural language processing models.Select the answer that correctly completes the sentence.

1. Microsoft Copilot Studio

2. Microsoft Bot Framework

3. Azure Health Bot

33. Which machine learning algorithm is mostly used for predicting the values of categorical variables.

1. Logistic regression

2. K-Means

3. Linear regression

34. Using RFM ( Recency, Frequency, Monetary) values to identify segments of a customer base is an example of _____Select the answer that correctly completes the sentence.

1. Regularization

2. Clustering

3. Classification

4. Regression

35. Which of the provided options is considered the calculated probability of a correct image classification?

1. Accuracy

2. Sentiment

3. Root Mean Square Error

4. Confidence

36. You have published your Language Understanding application. What information does a client application developer need to get predictions from it?

1. The Azure credentials of the user who published the Language Understanding application

2. The endpoint and key for the application's prediction resource

3. The endpoint and key for the application's authoring resource

37. You need to deploy a real-time inference pipeline as a service for others to consume. Select the appropriate option to where you must deploy the model.

1. From Azure machine learning designer to Azure Kubernetes service

2. From Azure machine learning designer to Local web service

3. From Azure machine learning designer to Azure machine learning compute.

4. From Azure machine learning designer to Azure container instances

38. You have created a training pipeline in azure machine learning designer and now you want to experiment with the pipeline/code for which you need scalable clusters of virtual machines. What kind of compute target is suitable for the task mentioned.

1. Inference Clusters

2. Compute Clusters

3. Compute Instances

39. You need to convert handwritten notes into digital text. Which type of computer vision should you use?

1. Object detection

2. Image classification

3. Facial detection

4. Optical Character Recognition (OCR)

40. You are working as a solution architect for an online retail store and have been tasked to create a service that will go through all the reviews of a product and should be able to detect if a customer is happy with the product or upset. Which type of AI workload should you use?

1. Natural language processing

2. Semantic segmentation

3. Regression

4. Anomaly detection

Frequently Asked Questions ( FAQs ) - Microsoft Azure AI Fundamentals ( AI - 900 )

1. What is the Azure AI Fundamentals certification?

The Azure AI Fundamentals certification is an entry-level Microsoft certification that validates foundational knowledge of artificial intelligence concepts and Azure AI services. It is designed for beginners who want to understand AI workloads, machine learning, NLP, computer vision, and responsible AI principles.

2. What is the exam code for Azure AI Fundamentals?

The official exam code for Azure AI Fundamentals is AI-900.

3. Is coding required for the AI-900 certification exam?

No. The AI-900 exam does not require advanced programming skills. The certification focuses mainly on foundational AI concepts, Azure AI services, and real-world AI use cases rather than deep software development.

4. Who should take the Azure AI Fundamentals certification?

The certification is ideal for:

• Beginners in AI and cloud computing

• Students and freshers

• Business professionals

• Data and AI enthusiasts

• IT professionals exploring artificial intelligence

• Professionals planning advanced Microsoft AI certifications

5. How difficult is the Azure AI Fundamentals exam?

The AI-900 exam is considered beginner-friendly compared to advanced Microsoft certifications. Candidates with basic cloud knowledge and consistent preparation can successfully pass the exam using official Microsoft learning resources and practice questions.

6. What topics are covered in the AI-900 exam?

The exam commonly covers:

• AI workloads and considerations

• Machine learning fundamentals

• Computer vision

• Natural language processing (NLP)

• Conversational AI

• Generative AI basics

• Responsible AI principles

• Azure AI services

7. How many questions are there in the Azure AI Fundamentals exam?

The exam typically contains around 40–60 questions, including multiple-choice and scenario-based questions.

8. What is the passing score for the AI-900 exam?

Candidates generally need a score of 700 out of 1000 to pass the Azure AI Fundamentals certification exam.

9. Are practice questions useful for AI-900 preparation?

Yes. Practice questions help candidates:

• Understand exam patterns

• Improve confidence

• Identify weak areas

• Learn Microsoft AI terminology

• Prepare for scenario-based questions

Regular practice significantly improves exam readiness

10. What are the best official resources for AI-900 preparation?

Some of the best official resources include:

• Microsoft Learn AI-900 learning path

• Official AI-900 skills outline

• Azure AI documentation

• Microsoft practice assessments

• Azure AI service documentation

These resources align directly with the latest Microsoft certification objectives.

11. Can the Azure AI Fundamentals certification help my career?

Yes. The certification helps validate foundational AI and cloud knowledge, making it useful for entry-level cloud, AI, automation, and digital transformation roles. It also supports future learning paths toward advanced Azure AI certifications.

12. Does the Azure AI Fundamentals certification expire?

Microsoft certification policies can change over time. Candidates should always verify the latest certification validity and renewal information through official Microsoft certification portals.

13. Is hands-on Azure experience necessary for the AI-900 exam?

Hands-on experience is not mandatory, but basic exposure to Azure AI services greatly improves conceptual understanding and helps candidates answer scenario-based questions more confidently.

14. What jobs can I apply for after earning the AI-900 certification?

While AI-900 is a foundational certification, it can support career paths such as:

• Junior Cloud Associate

• AI Support Associate

• Technical Consultant

• Data & AI Beginner Roles

• Cloud Support Specialist

• Business Technology Analyst

15. How long does it take to prepare for the Azure AI Fundamentals certification?

Preparation time depends on prior experience. Beginners typically spend a few weeks learning AI fundamentals, Azure AI services, and practicing exam-style questions consistently before attempting the certification exam.