As a candidate for this Microsoft Certification, you’re at the beginning of your career in AI solution development. For this exam, you should have conceptual knowledge of AI solutions in Azure and the foundational technical skills to work with them. You also need knowledge of Python coding syntax and programming techniques, and you should be familiar with Azure resources. Note The bullets that follow each of the skills measured are intended to illustrate how we are assessing that skill. Related topics may be covered in the exam. Note Most questions cover features that are general availability (GA). The exam may contain questions on Preview features if those features are commonly used. You should be familiar with REST APIs, SDKs, and CLIs. Important The English language version of this certification was updated on April 15, 2026. Review the study guide linked on the Exam AI-900 and Exam AI-901 pages for details about recent changes.

As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that leverage Azure AI. Your responsibilities include participating in all phases of AI solutions development, including: Requirements definition and design Development Deployment Integration Maintenance Performance tuning Monitoring You work with solution architects to translate their vision. You also work with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to: Build complete and secure end-to-end AI solutions. Integrate AI capabilities in other applications and solutions. As an Azure AI engineer, you have experience developing solutions that use languages such as: Python C# You should be able to use Representational State Transfer (REST) APIs and SDKs to build secure image processing, video processing, natural language processing, knowledge mining, and generative AI solutions on Azure. You should: Understand the components that make up the Azure AI portfolio and the available data storage options. Be able to apply responsible AI principles.

To earn this Microsoft Applied Skills credential, learners demonstrate the ability to develop AI agents by using Azure OpenAI Service and the Semantic Kernel SDK. Candidates for this credential should be familiar with Visual Studio Code, C# programming, and Azure OpenAI.

To earn this Microsoft Applied Skills credential, learners demonstrate the ability to build computer vision solutions by using Azure AI Vision. Candidates for this credential should have a solid understanding of working with Azure AI Vision models, both prebuilt and custom, through Vision Studio and in code. They should also have experience programming in either Python or C#, be familiar with the Azure portal, and be comfortable provisioning Azure AI resources.

To earn this Microsoft Applied Skills credential, learners demonstrate the ability to develop generative AI solutions with Azure OpenAI Service. Candidates for this credential should be familiar with Azure services and have experience developing applications by using C# or Python.

To earn this Microsoft Applied Skills credential, learners demonstrate the ability to create a natural language processing (NLP) solution by using Azure AI Language. Candidates for this credential should have a solid understanding of creating and using various Azure NLP models through both Language Studio and in code, including custom models. They should also have experience programming in either Python or C#, be familiar with the Azure portal, and be comfortable provisioning Azure AI resources.

To earn this Microsoft Applied Skills credential, learners demonstrate the ability to create and implement Azure AI Document Intelligence solutions. Candidates for this credential should have a solid understanding of creating and using Document Intelligence models through both Document Intelligence Studio and in code. They should also have experience programming in either Python or C#, be familiar with the Azure portal, and be comfortable provisioning Azure AI resources.