Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.

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.

Artificial Intelligence (AI) in increasingly prevalent in the software applications we use every day; including digital assistants in our homes and cellphones, automotive technology in the vehicles that take us to work, and smart productivity applications that help us do our jobs when we get there.

So you want to become an AI Engineer?

Your journey starts with an exploration of the core concepts and principles on which artificial intelligence is based, and an overview of the Microsoft Azure services you can use to develop AI solutions.