Microsoft AI-102 Exam Practice Questions

Course Provided by:Neil Baal
Course Taken on: Udemy
star_border star_border star_border star_border star_border 0

Description

The course includes the below exam concepts:


Plan and manage an Azure AI solution (15–20%)

Select the appropriate Azure AI service

  • Select the appropriate service for a computer vision solution

  • Select the appropriate service for a natural language processing solution

  • Select the appropriate service for a decision support solution

  • Select the appropriate service for a speech solution

  • Select the appropriate service for a generative AI solution

  • Select the appropriate service for a document intelligence solution

  • Select the appropriate service for a knowledge mining solution

Plan, create and deploy an Azure AI service

  • Plan for a solution that meets Responsible AI principles

  • Create an Azure AI resource

  • Determine a default endpoint for a service

  • Integrate Azure AI services into a continuous integration and continuous delivery (CI/CD) pipeline

  • Plan and implement a container deployment

Manage, monitor and secure an Azure AI service

  • Configure diagnostic logging

  • Monitor an Azure AI resource

  • Manage costs for Azure AI services

  • Manage account keys

  • Protect account keys by using Azure Key Vault

  • Manage authentication for an Azure AI Service resource

  • Manage private communications

Implement decision support solutions (10–15%)

Create decision support solutions for data monitoring and anomaly detection

  • Implement a univariate anomaly detection solution with Azure AI Anomaly Detector

  • Implement a multivariate anomaly detection solution Azure AI Anomaly Detector

  • Implement a data monitoring solution with Azure AI Metrics Advisor

Create decision support solutions for content delivery

  • Implement a text moderation solution with Azure AI Content Safety

  • Implement an image moderation solution with Azure AI Content Safety

  • Implement a content personalization solution with Azure AI Personalizer

Implement computer vision solutions (15–20%)

Analyze images

  • Select visual features to meet image processing requirements

  • Detect objects in images and generate image tags

  • Include image analysis features in an image processing request

  • Interpret image processing responses

  • Extract text from images using Azure AI Vision

  • Convert handwritten text using Azure AI Vision

Implement custom computer vision models by using Azure AI Vision

  • Choose between image classification and object detection models

  • Label images

  • Train a custom image model, including image classification and object detection

  • Evaluate custom vision model metrics

  • Publish a custom vision model

  • Consume a custom vision model

Analyze videos

  • Use Azure AI Video Indexer to extract insights from a video or live stream

  • Use Azure AI Vision Spatial Analysis to detect presence and movement of people in video

Implement natural language processing solutions (30–35%)

Analyze text by using Azure AI Language

  • Extract key phrases

  • Extract entities

  • Determine sentiment of text

  • Detect the language used in text

  • Detect personally identifiable information (PII) in text

Process speech by using Azure AI Speech

  • Implement text-to-speech

  • Implement speech-to-text

  • Improve text-to-speech by using Speech Synthesis Markup Language (SSML)

  • Implement custom speech solutions

  • Implement intent recognition

  • Implement keyword recognition

Translate language

  • Translate text and documents by using the Azure AI Translator service

  • Implement custom translation, including training, improving, and publishing a custom model

  • Translate speech-to-speech by using the Azure AI Speech service

  • Translate speech-to-text by using the Azure AI Speech service

  • Translate to multiple languages simultaneously

Implement and manage a language understanding model by using Azure AI Language

  • Create intents and add utterances

  • Create entities

  • Train, evaluate, deploy, and test a language understanding model

  • Optimize a language understanding model

  • Consume a language model from a client application

  • Backup and recover language understanding models

Create a question answering solution by using Azure AI Language

  • Create a question answering project

  • Add question-and-answer pairs manually

  • Import sources

  • 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

  • Create a multi-language question answering solution

Implement knowledge mining and document intelligence solutions (10–15%)

Implement an Azure Cognitive Search solution

  • Provision a Cognitive Search resource

  • Create data sources

  • Create an index

  • Define a skillset

  • Implement custom skills and include them in a skillset

  • Create and run an indexer

  • Query an index, including syntax, sorting, filtering, and wildcards

  • Manage Knowledge Store projections, including file, object, and table projections

Implement an Azure AI Document Intelligence solution

  • Provision a Document Intelligence resource

  • Use prebuilt models to extract data from documents

  • Implement a custom document intelligence model

  • Train, test, and publish a custom document intelligence model

  • Create a composed document intelligence model

  • Implement a document intelligence model as a custom Azure Cognitive Search skill

Implement generative AI solutions (10–15%)

Use Azure OpenAI Service to generate content

  • Provision an Azure OpenAI Service resource

  • Select and deploy an Azure OpenAI model

  • Submit prompts to generate natural language

  • Submit prompts to generate code

  • Use the DALL-E model to generate images

  • Use Azure OpenAI APIs to submit prompts and receive responses

Optimize generative AI

  • Configure parameters to control generative behavior

  • Apply prompt engineering techniques to improve responses

  • Use your own data with an Azure OpenAI model

  • Fine-tune an Azure OpenAI model

Requrirements

Basic understanding of Azure AI concepts

Course Includes

  • 3 practice tests
  • Access on mobile
  • Full lifetime access