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As a Microsoft Azure AI engineer, you build, manage, and deploy AI solutions that make the most of:
Your responsibilities include participating in all phases of AI solutions development, including:
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.
Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services and Azure Applied AI services.
Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.
They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.
Candidates for this exam should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.
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