The "AI-102 Azure AI Engineer Associate AI102 PT Practice Test" offers you a unique opportunity to prepare comprehensively and practically for the AI-102 certification exam, which qualifies you as an Azure AI Engineer Associate. This practice test has been specially designed to provide a complete immersion in essential topics related to artificial intelligence engineering in the Azure environment.
By participating in this practice test, you will have access to a series of carefully selected questions that address the most relevant concepts and scenarios for artificial intelligence engineering in Azure. Each question not only tests your knowledge but also challenges you to apply that knowledge in practical situations, similar to what you will encounter in the real world.
Candidates for the AI-102 Exam: Designing and implementing a Microsoft Azure Ai Solution Build, manage and deploy AI solutions that enjoy Azure's cognitive services, Azure cognitive research and Microsoft Bot structure.
Skills measured
Plan and manage an Azure Cognitive Services solution (15-20%)
Implement Computer Vision solutions (20-25%)
Implement natural language processing solutions (20-25%)
Implement knowledge mining solutions (15-20%)
Implement conversational AI solutions (15-20%)
The Exam consists of questions covering the following modules/topics:
Plan and Manage an Azure Cognitive Services Solution (15-20%)
Select the appropriate Cognitive Services resource
Plan and configure security for a Cognitive Services solution
Create a Cognitive Services resource
Plan and implement Cognitive Services containers
Implement Computer Vision Solutions (20-25%)
Analyze images by using the Computer Vision API
Extract text from images
Extract facial information from images
Implement image classification by using the Custom Vision service
Portal
Implement an object detection solution by using the Custom Vision service
Analyze video by using Azure Video Analyzer for Media (formerly Video Indexer)
Implement Natural Language Processing Solutions (20-25%)
Analyze text by using the Text Analytics service
Manage speech by using the Speech service
Translate language
Build an initial language model by using Language Understanding Service (LUIS)
Iterate on and optimize a language model by using LUIS
Manage a LUIS model
Implement Knowledge Mining Solutions (15-20%)
Implement a Cognitive Search solution
Implement an enrichment pipeline
Implement a knowledge store
Manage a Cognitive Search solution
Manage indexing
Implement Conversational AI Solutions (15-20%)
Create a knowledge base by using QnA Maker
Design and implement conversation flow
Create a bot by using the Bot Framework SDK
Create a bot by using the Bot Framework Composer
Integrate Cognitive Services into a bot
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.