After passing this test, campaigners get an instrument from Microsoft that helps them to demonstrate their proficiency to their guests and employers.
Motifs of AI- 102 Designing and enforcing an Azure AI result test
Campaigners should seize the examination motifs before they begin of medication. Because it ’ll extremely grease them in touch the core. Our AI- 102 dumps will include the following motifs
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1. Dissect result conditions (25- 30)
Recommend Cognitive Services APIs to meet business conditions
• elect the processing armature for a result
• elect the applicable data processing technologies
• elect the applicable AI models and services
• Identify factors and technologies needed to connect service endpoints
• Identify robotization conditions
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Chart security conditions to tools, technologies, and processes
• Identify processes and regulations demanded to conform to data sequestration, protection, and nonsupervisory conditions
• Identify which druggies and groups have access to information and interfaces
• Identify applicable tools for a result
• Identify auditing conditions
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Elect the software, services, and storehouse needed to support a result
• Identify applicable services and tools for a result
• Identify integration points with other Microsoft services
• Identify storehouse needed to store logging, bot state data, and Cognitive Services affair
Design AI results (40- 45) | Design results that include one or further channels
• Define an AI operation workflow process
• Design a strategy for ingest and egress data
• Design the integration point between multiple workflows and channels
• Design channels that use AI apps
• Design channels that call Azure Machine Learning models
• elect an AI result that meet cost constraints
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Design results that uses Cognitive Services
• Design results that use vision, speech, language, knowledge, hunt, and anomaly discovery APIs
Design results that apply the Bot Framework
• Integrate bots and AI results
• Design bot services that use Language Understanding (LUIS)
• Design bots that integrate with channels
• Integrate bots with Azure app services and Azure operation perceptivity
Design the cipher structure to support a result
• Identify whether to produce a GPU, FPGA, or CPU- grounded result
• Identify whether to use a pall- grounded, on- demesne, or mongrel cipher structure
• elect a cipher result that meets cost constraints
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