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|  Microsoft AI-102 : Designing and Implementing a Microsoft Azure AI Solution Exam Questions, MCQs and Practice TestPractice Test Organized by Shahid nazir | 
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Exam Number : AI-102
Exam Name : Designing and Implementing a Microsoft Azure AI Solution
Vendor Name : Microsoft
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Exam Number: AI-102
Exam Name : Designing and Implementing a Microsoft Azure AI Solution
Exam TOPICS
The Cisco Customer Success Manager (DTCSM) v2.1 course gives you the confidence and competence to fulfill the Customer Success Manager (CSM) role successfully, helping your customers realize value from their solutions and achieve their business outcomes. The course offers experiential learning through practical exercises using situations based on real-life use cases and case studies. In this highly interactive course, you can practice and gain confidence in fulfilling core tasks using best-practice tools and methodologies while receiving feedback from the facilitator and your peers.
Candidates for the Azure AI Engineer Associate certification should have subject matter expertise building, managing, and deploying 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.
Azure AI Engineers 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 certification 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 principle.
Plan and manage an Azure Cognitive Services solution
Implement Computer Vision solutions                 
Implement natural language processing solutions     
Implement knowledge mining solutions                
Implement conversational AI solutions               
Plan and Manage an Azure Cognitive Services Solution (15-20%)
Select the appropriate Cognitive Services resource
 select the appropriate cognitive service for a vision solution				
 select the appropriate cognitive service for a language analysis solution     
 select the appropriate cognitive Service for a decision support solution      
 select the appropriate cognitive service for a speech solution                
Plan and configure security for a Cognitive Services solution                   
 manage Cognitive Services account keys                                        
 manage authentication for a resource                                          
 secure Cognitive Services by using Azure Virtual Network                      
 plan for a solution that meets responsible AI principles                      
Create a Cognitive Services resource                                            
 create a Cognitive Services resource                                          
 configure diagnostic logging for a Cognitive Services resource                
 manage Cognitive Services costs                                               
 monitor a cognitive service                                                   
 implement a privacy policy in Cognitive Services                              
Plan and implement Cognitive Services containers                                
 identify when to deploy to a container                                        
 containerize Cognitive Services (including Computer Vision API, Face API, Text Analytics,
Speech, Form Recognizer)
 deploy Cognitive Services Containers in Microsoft Azure
Implement Computer Vision Solutions (20-25%)
Analyze images by using the Computer Vision API
 retrieve image descriptions and tags by using the Computer Vision API		
 identify landmarks and celebrities by using the Computer Vision API       
 detect brands in images by using the Computer Vision API                  
 moderate content in images by using the Computer Vision API               
 generate thumbnails by using the Computer Vision API                      
Extract text from images                                                    
 extract text from images or PDFs by using the Computer Vision service     
 extract information using pre-built models in Form Recognizer             
 build and optimize a custom model for Form Recognizer                     
Extract facial information from images                                      
 detect faces in an image by using the Face API                            
 recognize faces in an image by using the Face API                         
 analyze facial attributes by using the Face API                           
 match similar faces by using the Face API                                 
Implement image classification by using the Custom Vision service           
 label images by using the Computer Vision Portal                          
 train a custom image classification model in the Custom Vision Portal     
 train a custom image classification model by using the SDK                
 manage model iterations                                                   
 evaluate classification model metrics                                     
 publish a trained iteration of a model                                    
 export a model in an appropriate format for a specific target             
 consume a classification model from a client application                  
 deploy image classification custom models to containers                   
Implement an object detection solution by using the Custom Vision service   
 label images with bounding boxes by using the Computer Vision Portal      
 train a custom object detection model by using the Custom Vision Portal   
 train a custom object detection model by using the SDK                    
 manage model iterations                                                   
 evaluate object detection model metrics                                   
 publish a trained iteration of a model                                    
 consume an object detection model from a client application               
 deploy custom object detection models to containers                       
Analyze video by using Video Indexer                                        
 process a video                                                           
 extract insights from a video                                             
 moderate content in a video                                               
 customize the Brands model used by Video Indexer                          
 customize the Language model used by Video Indexer by using the Custom Speech service
 customize the Person model used by Video Indexer								
 extract insights from a live stream of video data                             
Implement Natural Language Processing Solutions (20-25%)                        
Analyze text by using the Text Analytics service                                
 retrieve and process key phrases                                              
 retrieve and process entity information (people, places, urls, etc.)          
 retrieve and process sentiment                                                
 detect the language used in text                                              
Manage speech by using the Speech service                                       
 implement text-to-speech                                                      
 customize text-to-speech                                                      
 implement speech-to-text                                                      
 improve speech-to-text accuracy                                               
 improve text-to-speech accuracy                                               
 implement intent recognition                                                  
Translate language                                                              
 translate text by using the Translator service                                
 translate speech-to-speech by using the Speech service                        
 translate speech-to-text by using the Speech service                          
Build an initial language model by using Language Understanding Service (LUIS)  
 create intents and entities based on a schema, and then add utterances        
 create complex hierarchical entities                                          
o use this instead of roles                                                     
 train and deploy a model                                                      
Iterate on and optimize a language model by using LUIS                          
 implement phrase lists                                                        
 implement a model as a feature (i.e. prebuilt entities)                       
 manage punctuation and diacritics                                             
 implement active learning                                                     
 monitor and correct data imbalances                                           
 implement patterns                                                            
Manage a LUIS model                                                             
 manage collaborators                                                          
 manage versioning                                                             
 publish a model through the portal or in a container                          
 export a LUIS package                                                         
 deploy a LUIS package to a container                                          
 integrate Bot Framework (LUDown) to run outside of the LUIS portal            
Implement Knowledge Mining Solutions (15-20%)                                   
Implement a Cognitive Search solution                                           
 create data sources                                                           
 define an index                                                               
 create and run an indexer                                                     
 query an index                                                                
 configure an index to support autocomplete and autosuggest                    
 boost results based on relevance                                              
 implement synonyms                                                            
Implement an enrichment pipeline                                                
 attach a Cognitive Services account to a skillset                             
 select and include built-in skills for documents                              
 implement custom skills and include them in a skillset                        
Implement a knowledge store                                                     
 define file projections                                                       
 define object projections                                                     
 define table projections                                                      
 query projections                                                             
Manage a Cognitive Search solution                                              
 provision Cognitive Search                                                    
 configure security for Cognitive Search                                       
 configure scalability for Cognitive Search                                    
Manage indexing                                                                 
 manage re-indexing                                                            
 rebuild indexes                                                               
 schedule indexing                                                             
 monitor indexing                                                              
 implement incremental indexing                                                
 manage concurrency                                                            
 push data to an index                                                         
 troubleshoot indexing for a pipeline                                          
Implement Conversational AI Solutions (15-20%)                                  
Create a knowledge base by using QnA Maker                                      
 create a QnA Maker service                                                    
 create a knowledge base                                                       
 import a knowledge base                                                       
 train and test a knowledge base                                               
 publish a knowledge base                                                      
 create a multi-turn conversation                                              
 add alternate phrasing                                                        
 add chit-chat to a knowledge base                                             
 export a knowledge base                                                       
 add active learning to a knowledge base                                       
 manage collaborators                                                          
Design and implement conversation flow                                          
 design conversation logic for a bot                                           
 create and evaluate *.chat file conversations by using the Bot Framework Emulator
 choose an appropriate conversational model for a bot, including activity handlers and dialogs
Create a bot by using the Bot Framework SDK
 use the Bot Framework SDK to create a bot from a template
 implement activity handlers and dialogs                  
 use Turn Context                                         
 test a bot using the Bot Framework Emulator              
 deploy a bot to Azure                                    
Create a bot by using the Bot Framework Composer           
 implement dialogs                                        
 maintain state                                           
 implement logging for a bot conversation                 
 implement prompts for user input                         
 troubleshoot a conversational bot                        
 test a bot                                               
 publish a bot                                            
 add language generation for a response                   
 design and implement adaptive cards                      
Integrate Cognitive Services into a bot                    
 integrate a QnA Maker service                            
 integrate a LUIS service                                 
 integrate a Speech service                               
 integrate Dispatch for multiple language models          
 manage keys in app settings file                         
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