Exam AI-102: Designing and Implementing a Microsoft Azure AI

About this course

Azure AI engineers are responsible for creating, maintaining, and deploying AI solutions that leverage Azure Cognitive Services and Azure services. They are involved in all stages of development, including requirements gathering, design, development, deployment, integration, maintenance, performance tuning, and monitoring.Working closely with solution architects, these professionals collaborate with data scientists, data engineers, IoT specialists, infrastructure administrators, and other software developers to create comprehensive AI solutions from start to finish.To build secure and effective image processing, video processing, natural language processing (NLP), knowledge mining, and conversational AI solutions on Azure, Azure AI engineers should be proficient in using REST-based APIs and software development kits (SDKs) and have experience with programming languages such as Python or C#. They should also be well-versed in various methods for implementing AI solutions and possess knowledge of the different components that make up the Azure AI portfolio, as well as the available data storage options. Moreover, Azure AI engineers must have a strong grasp of responsible AI principles and be capable of applying them effectively.This exam measures your proficiency in the following technical areas: devising and supervising an Azure AI solution; executing image and video processing solutions; executing natural language processing solutions; executing knowledge mining solutions; and executing conversational AI solutions. The AI-102 Designing and Implementing an Azure AI Solution is designed for software developers who wish to construct AI-driven applications that utilize Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.

Course objectives

• Master the components of the Azure AI portfolio
• Understand and utilize REST-based APIs
• Collaborate with data scientists and engineers to create AI-driven applications