Exam AI-100: Designing and Implementing an Azure AI Solution
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Overview
Candidates for this exam should have subject matter expertise using cognitive services, machine learning, and knowledge mining to architect and implement Microsoft AI solutions involving natural language processing, speech, computer vision, and conversational AI.
Responsibilities for an Azure AI Engineer include analyzing requirements for AI solutions, recommending the appropriate tools and technologies, and designing and implementing AI solutions that meet scalability and performance requirements.
Azure AI Engineers translate the vision from solution architects and work with data scientists, data engineers, IoT specialists, and software developers to build complete end-to-end solutions.
A candidate for this exam should have knowledge and experience designing and implementing AI apps and agents that use Microsoft Azure Cognitive Services, Azure Bot Service, Azure Cognitive Search, and data storage in Azure. In addition, a candidate should be able to recommend solutions that use open source technologies, understand the components that make up the Azure AI portfolio and the available data storage options, and understand when a custom API should be developed to meet specific requirements.
Skills Measured
- Analyze solution requirements (25-30%)
- Design AI solutions (40-45%)
- Implement and monitor AI solutions (25-30%)
Getting Started
Getting Started
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Exam AI-100: Skills Outline
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In this session we will break down the Objective Domains and information supporting those Objective Domains in order to prepare for the AI-100 Exam. AI-100 is a great exam...
AI-100 Videos
Learning Paths
Microsoft Cognitive Services offers pre-built functionality to enable computer vision functionality in your applications. Learn how to use the Cognitive Vision Services to detect faces, tag and classify images, and identify objects
Levels: Beginner
Roles: AI Engineer
Modules
Learn how to implement the Speech services found in Azure Cognitive Services by performing speech-to-text transcription, synthesize text input to speech, perform speech translation, and implement speaker recognition in your AI infused applications
Levels: Intermediate
Roles: AI Engineer, Developer
Modules
In this learning path, find out how to build a chat bot to interact with customers using text, graphics, or speech with extras from QnA Maker and LUIS.
Levels: Beginner
Roles: AI Engineer
Modules
Learn how to use Cognitive Language Services to analyze text, determine intent, detect adult themes, and process natural language input
Levels: Beginner
Roles: AI Engineer
Modules