Microsoft Azure AI Fundamentals – AI-900 Exam Detailed Overview (2025)

Looking to ace the Microsoft Certified Azure AI Fundamentals (AI-900) exam? This blog provides everything you need to not just pass the exam, but also to gain a solid understanding of AI and machine learning concepts with Azure’s powerful tools and services.

What Is Azure AI Fundamentals Certification? ^

AI 900 certification is a fundamental grade certification for data scientists to have an idea of how to apply AI and Machine Learning in their profession. Also, it certifies you for using Azure services related to ML and AI. In addition, we can use the AI 900 Microsoft Azure AI Fundamentals certification exam as an important tool for demonstrating a thorough understanding of general ML and AI workloads.

Why Use Azure AI Solutions? ^

• Gives a cloud platform for implementing AI Solutions
• Provide no-code ML models for processing data.
• Implement and monitor AI solutions
• You can design AI as cost-effective Intelligent Edge solutions.
• You can design and identify data governance, and requirements.

Also read: Azure Core Identity Services – Azure AD & MFA

AI 900 | Benefits ^

• As a result of the rocketing growth of AI, the importance of Azure AI Engineers is also visible.
• The capabilities of translating the vision of cloud architects for the development of end-to-end solutions using AI and ML on Azure.
• It will improve your earning potential.
• Azure AI engineers have to work in collaboration with data engineers, data scientists, AI developers, and IoT specialists as all of these roles are interdependent.

Check this article on Azure Machine Learning Studio

AI 900 Exam Details ^

• Name of the Exam: Microsoft Azure AI Fundamentals
• Exam Code: AI-900
• Technology: Microsoft Azure
• Prerequisites: None
• Registration Fee: 99 USD (Price based on the country or region in which the exam is proctored)
• Duration: 45 minutes
• Exam Language: English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Russian, Indonesian (Indonesia), Arabic (Saudi Arabia), Chinese (Traditional), Italian

You can apply for Microsoft Azure AI Fundamentals certification by visiting the official Microsoft page.

Pre-requisites For AI-900 Certification ^

There are no prerequisites required to opt for this certification.

AI 900 Exam Topics ^

1. Artificial Intelligence Workloads and Considerations (15–20%)

• Identify features of common AI workloads
  • Features of content moderation and personalization workloads
  • Features of computer vision workloads
  • Features of natural language processing workloads
  • Features of knowledge mining workloads
  • Features of document intelligence workloads
  • Features of generative AI workloads.
• Identify guiding principles for responsible AI
  • Considerations for fairness in an AI solution
  • Considerations for reliability and safety in an AI solution
  • Considerations for privacy and security in an AI solution
  • Considerations for inclusiveness in an AI solution
  • Considerations for transparency in an AI solution
  • Considerations for accountability in an AI solution

2. Fundamental Principles of Machine Learning on Azure (20–25%)

• Identify common machine-learning techniques
  • Identify regression machine learning scenarios
  • Identify classification machine learning scenarios
  • Identify clustering machine learning scenarios
  • Identify features of deep learning techniques
• Describe core machine learning concepts
  • Identify features and labels in a dataset for machine learning
  • Describe how training and validation datasets are used in machine learning
• Describe Azure Machine Learning capabilities
  • Capabilities of automated machine learning
  • Data and compute services for data science and machine learning
  • Model management and deployment capabilities in Azure Machine Learning

3. Features of Computer Vision Workloads on Azure (15–20%)

• Identify common types of computer vision solution
  • Features of image classification solutions
  • Features of object detection solutions
  • Features of optical character recognition solutions
  • Features of facial detection and facial analysis solutions
• Identify Azure tools and services for computer vision tasks
  • Capabilities of the Azure AI Vision service
  • Capabilities of the Azure AI Face Detection service
  • Describe the capabilities of the Azure AI Video Indexer service

4. Features of Natural Language Processing (NLP) Workloads on Azure (15–20%)

• Identify features of common NLP Workload Scenarios
  • Features and uses for keyphrase extraction
  • Features and uses for entity recognition
  • Features and uses for sentiment analysis
  • Features and uses for language modeling
  • Features and uses for speech recognition and synthesis
  • Features and uses for translation
• Identify Azure tools and services for NLP workloads
  • Capabilities of the Azure AI-Language service
  • Capabilities of the Azure AI Speech Service

5. Features of Generative AI Workloads on Azure (15–20%)

• Identify features of generative AI solutions
  • Features of generative AI models
  • Common scenarios for generative AI
  • Responsible AI considerations for generative AI
• Identify capabilities of Azure OpenAI Service
  • Natural language generation capabilities of Azure OpenAI Service
  • Code generation capabilities of Azure OpenAI Service
  • Image generation capabilities of Azure OpenAI Service

AI 900 Hands-On Guide ^

To understand the concepts of AI fundamentals and from the exam point of view, we have a complete Step-by-Step guide for Microsoft Azure AI Fundamentals [AI900]: Step-by-Step Activity Guides (Hands-On Labs) to help you learn.

Who This Certification Is For? ^

If you are waiting to know that can you do this certification? Well, here is the answer:

• Candidates who are interested in Machine Learning and AI.
• IT professionals who have a thorough knowledge of Microsoft Azure.
• Those working as Azure Engineers.
• People working as Data Scientists.
• Candidates who architect and implement cloud solutions.

AI 900 Exam Day Tips ^

• Run a System Check before the exam.
• There can be a variation in the exam question types such as fill in the blanks, true or false, multiple answers, multiple-choice, drag-and-drop, and fill the missing modules in the given pipeline, so be prepared!
• Be careful and pace yourself on the questions to avoid getting stuck on one question for a long time. Just skip the unfamiliar questions and come back later.
• Breaks will not be allowed during the exam.

Related/References

• Microsoft Azure AI Fundamentals [AI-900]: Step By Step Activity Guides (Hands-On Labs)
• Automated Machine Learning | Azure | Pros & Cons
• Object Detection and Tracking in Azure Machine Learning
• Azure Machine Learning Studio
• Azure Cognitive Services (Overview & Types)

Next Task: Enhance Your Azure AI/ML Skills