AI-102: Designing and Implementing a Microsoft Azure AI Sol.

**4 Practice Tests. 230 real exam questions.** This exams measures your ability to accomplish the following technical tasks: plan and manage an Azure AI solution; implement image and video processing solutions; implement natural language processing solutions; implement knowledge mining solutions; and implement conversational AI solutions. **Skills measured** This list contains the skills measured on the exam required for this certification. For more detailed information, visit the exam details page and review the study guide. - Plan and manage an Azure AI solution - Implement image and video processing solutions - Implement natural language processing solutions - Implement knowledge mining solutions - Implement conversational AI solutions Microsoft Azure AI engineers build, manage, and deploy AI solutions that make the most of Azure Cognitive Services and Azure services. Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, integration, maintenance, performance tuning, and monitoring. These professionals work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, infrastructure administrators, and other software developers to build complete end-to-end AI solutions. Azure AI engineers have experience developing solutions that use languages such as Python or C# and should be able to use REST-based APIs and software development kits (SDKs) to build secure image processing, video processing, natural language processing (NLP), knowledge mining, and conversational AI solutions on Azure. They should be familiar with all methods of implementing AI solutions. Plus, they understand the components that make up the Azure AI portfolio and the available data storage options. Azure AI engineers also need to understand and be able to apply responsible AI principles.