As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that make the most of:
- Azure Cognitive Services.
- Azure Applied AI services.
Your responsibilities include participating in all phases of AI solutions development, including:
- Requirements definition and design
- Performance tuning
You work with solution architects to translate their vision and with data scientists, data engineers, Internet of Things (IoT) specialists, infrastructure administrators, and other software developers to build complete end-to-end AI solutions.
As an Azure AI engineer, you have experience developing solutions that use languages such as:
You should be able to use Representational State Transfer (REST) APIs and SDK to build secure image processing, video processing, natural language processing, knowledge mining, and conversational AI solutions on Azure. You should be familiar with all methods of implementing AI solutions. Plus, you understand the components that make up the Azure AI portfolio and the available data storage options. As an Azure AI engineer, you also need to understand and be able to apply responsible AI principles.
The English language version of this exam was updated on August 23, 2023. Review the study guide linked in the “Tip” box for details about the latest changes. If a localized version of this exam is available, it will be updated approximately eight weeks after this date. While Microsoft makes every effort to update localized versions as noted, there may be times when the localized versions of this exam are not updated on this schedule.
Passing score: 700. Learn more about exam scores.
Cognitive Services has been renamed to Azure AI Services. Individual services have also been renamed. These changes will appear on the exam in late 2023. Learn more about Azure AI services.
Part of the requirements for: Microsoft Certified: Azure AI Engineer Associate
Related exams: noneGo to Learn Profile
- The English language version of this exam was updated on August 23, 2023. Review the study guide linked in the preceding “Tip” box for details about the skills measured and latest changes.
- Plan and manage an Azure AI solution (25–30%)
- Implement image and video processing solutions (15–20%)
- Implement natural language processing solutions (25–30%)
- Implement knowledge mining solutions (5–10%)
- Implement conversational AI solutions (15–20%)
Two ways to prepare
As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that make the most of Azure Cognitive Services and Azure Applied AI services.
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