MICROSOFT AI-102 RELIABLE EXAM SIMULATIONS - AI-102 RELIABLE BRAINDUMPS FREE

Microsoft AI-102 Reliable Exam Simulations - AI-102 Reliable Braindumps Free

Microsoft AI-102 Reliable Exam Simulations - AI-102 Reliable Braindumps Free

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We strive to use the simplest language to make the learners understand our AI-102 exam reference and the most intuitive method to express the complicated and obscure concepts. For the learners to fully understand our AI-102 test guide, we add the instances, simulation and diagrams to explain the contents which are very hard to understand. So after you use our AI-102 Exam Reference you will feel that our AI-102 test guide’ name matches with the reality.

Our practice exams are designed solely to help you get your AI-102 certification on your first try. A Microsoft AI-102 practice test will help you understand the exam inside out and you will get better marks overall. It is only because you have practical experience of the exam even before the exam itself. TestkingPDF offers authentic and up-to-date study material that every candidate can rely on for good preparation. Our top priority is to help you pass the Designing and Implementing a Microsoft Azure AI Solution (AI-102) exam on the first try. The key to passing the AI-102 exam on the first try is vigorous practice. And that's exactly what you'll get when you prepare from our material. Each format excels in its own way and helps you get success on the first attempt.

>> Microsoft AI-102 Reliable Exam Simulations <<

AI-102 Reliable Braindumps Free - New AI-102 Test Tutorial

Passing the Microsoft AI-102 is the primary concern. To pass the hard AI-102 exam on the first try, you must invest more time, effort, and money. To pass the AI-102 Exam, you must have the right Designing and Implementing a Microsoft Azure AI Solution AI-102 Exam Dumps, which are quite hard to get online. Get it right away to begin preparing. TestkingPDF is a reputable platform that has been providing valid, real, updated, and error-free Designing and Implementing a Microsoft Azure AI Solution AI-102 Exam Questions.

Prep Options to Choose

The preparation process for the exam is a vital step on your way of passing the test, that’s why you need to find the most actual and reliable resources. Microsoft offers two options for you to choose from online free training or instructor-led, which is a paid one. For example, the free training represents a collection of learning paths each of which contains the different number of modules, from one to five. Thus, you can choose which ones to follow: Prepare for AI engineering (1 module), Process and Translate Speech with Azure Cognitive Speech Services (2 modules), Create computer vision solutions with Azure Cognitive Services (3 modules), to name a few. The paid course is known to be Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution and lasts for 4 days. It is intended for software developers interested in developing skills to build AI infused apps that use Azure Cognitive Search and Services, and Microsoft Bot Framework.

In addition, you can check the Amazon website to find the books on the topics included in the exam to ace it from the first attempt. Only after the successful passing the AI-102 Exam you will earn the Microsoft Certified: Azure AI Engineer Associate certification. So, good luck!

The AI-102 certification exam is a great way for individuals to demonstrate their expertise in designing and implementing AI solutions on the Microsoft Azure platform. AI-102 exam consists of several topics, including the fundamentals of AI and machine learning, data preparation, model development and deployment, and monitoring and optimization. Candidates are required to have a deep understanding of each of these topics to pass the exam.

Microsoft AI-102 Exam Syllabus Topics:

TopicDetails

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, Languages, 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 Azure Video Analyzer for Media (formerly 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 Language 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 a initial language model by using Language Understanding Service (LUIS)- create intents and entities based on a schema, and add utterances
- create complex hierarchical entities
  • use this instead of roles

- train and deploy a model

Iterate on and optimize a language model by using Language Understanding- 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

Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q201-Q206):

NEW QUESTION # 201
You are examining the Language service output of an application.
The text analyzed is: Our tour guide took us up the Space Needle during our trip to Seattle last week.
The response contains the data shown in the following table.

Which Language service API is used 10 analyze the Text?

  • A. Key Phrase Extraction
  • B. Named Entity Recognition
  • C. Sentiment Analysis
  • D. Entity Linking

Answer: B


NEW QUESTION # 202
You are developing the knowledgebase.
You use Azure Video Analyzer for Media (previously Video indexer) to obtain transcripts of webinars.
You need to ensure that the solution meets the knowledgebase requirements.
What should you do?

  • A. Configure audio indexing for videos only
  • B. Enable multi-language detection for videos
  • C. Build a custom Person model for webinar presenters
  • D. Create a custom language model

Answer: A

Explanation:
Can search content in different formats, including video
Audio and video insights (multi-channels). When indexing by one channel, partial result for those models will be available.
Keywords extraction: Extracts keywords from speech and visual text.
Named entities extraction: Extracts brands, locations, and people from speech and visual text via natural language processing (NLP).
Topic inference: Makes inference of main topics from transcripts. The 2nd-level IPTC taxonomy is included.
Artifacts: Extracts rich set of "next level of details" artifacts for each of the models.
Sentiment analysis: Identifies positive, negative, and neutral sentiments from speech and visual text.
Reference:
https://docs.microsoft.com/en-us/azure/azure-video-analyzer/video-analyzer-for-media-docs/video-indexer-overv


NEW QUESTION # 203
You are developing a call to the Face API. The call must find similar faces from an existing list named employeefaces. The employeefaces list contains 60,000 images.
How should you complete the body of the HTTP request? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar


NEW QUESTION # 204
You are building a chatbot by using the Microsoft Bot Framework SDK.
You use an object named UserProfile to store user profile information and an object named ConversationData to store information related to a conversation.
You create the following state accessors to store both objects in state.
var userStateAccessors = _userState.CreateProperty<UserProfile>(nameof(UserProfile)); var conversationStateAccessors = _conversationState.CreateProperty<ConversationData>(nameof(ConversationData)); The state storage mechanism is set to Memory Storage.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-v4-state


NEW QUESTION # 205
You are building content for a video training solution.
You need to create narration to accompany the video content. The solution must use Custom Neural Voice.
What should you use to create a custom neural voice, and which service should you use to generate the narration? To answer, select the appropriate options in the answer area.
NOTE: Each correct answer is worth one point.

Answer:

Explanation:


NEW QUESTION # 206
......

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