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Skills measured as of May 2, 2023

  • Plan and manage an Azure AI solution (25–30%)

  • Implement image and video processing solutions (15–20%)

  • Implement natural language processing solutions (25–30%)

  • Implement knowledge mining solutions (5–10%)

  • Implement conversational AI solutions (15–20%)

Plan and manage an Azure AI solution (25–30%)

Select the appropriate Azure AI service

  • Select the appropriate service for a vision solution

  • Select the appropriate service for a language analysis solution

  • Select the appropriate service for a decision support solution

  • Select the appropriate service for a speech solution

  • Select the appropriate Applied AI services

Plan and configure security for Azure AI services

  • Manage account keys

  • Manage authentication for a resource

  • Secure services by using Azure Virtual Networks

  • Plan for a solution that meets Responsible AI principles

Create and manage an Azure AI service

  • Create an Azure AI resource

  • Configure diagnostic logging

  • Manage costs for Azure AI services

  • Monitor an Azure AI resource

Deploy Azure AI services

  • Determine a default endpoint for a service

  • Create a resource by using the Azure portal

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

  • Plan a container deployment

  • Implement prebuilt containers in a connected environment

Create solutions to detect anomalies and improve content

  • Create a solution that uses Anomaly Detector, part of Cognitive Services

  • Create a solution that uses Azure Content Moderator, part of Cognitive Services

  • Create a solution that uses Personalizer, part of Cognitive Services

  • Create a solution that uses Azure Metrics Advisor, part of Azure Applied AI Services

  • Create a solution that uses Azure Immersive Reader, part of Azure Applied AI Services

Implement image and video processing solutions (15–20%)

Analyze images

  • Select appropriate visual features to meet image processing requirements

  • Create an image processing request to include appropriate image analysis features

  • Interpret image processing responses

Extract text from images

  • Extract text from images or PDFs by using the Computer Vision service

  • Convert handwritten text by using the Computer Vision service

  • Extract information using prebuilt models in Azure Form Recognizer

  • Build and optimize a custom model for Azure Form Recognizer

Implement image classification and object detection by using the Custom Vision service, part of Azure Cognitive Services

  • Choose between image classification and object detection models

  • Specify model configuration options, including category, version, and compact

  • Label images

  • Train custom image models, including classifiers and detectors

  • Manage training iterations

  • Evaluate model metrics

  • Publish a trained iteration of a model

  • Export a model to run on a specific target

  • Implement a Custom Vision model as a Docker container

  • Interpret model responses

Process videos

  • Process a video by using Azure Video Indexer

  • Extract insights from a video or live stream by using Azure Video Indexer

  • Implement content moderation by using Azure Video Indexer

  • Integrate a custom language model into Azure Video Indexer

Implement natural language processing solutions (25–30%)

Analyze text

  • Retrieve and process key phrases

  • Retrieve and process entities

  • Retrieve and process sentiment

  • Detect the language used in text

  • Detect personally identifiable information (PII)

Process speech

  • Implement and customize text-to-speech

  • Implement and customize speech-to-text

  • Improve text-to-speech by using SSML and Custom Neural Voice

  • Improve speech-to-text by using phrase lists and Custom Speech

  • Implement intent recognition

  • Implement keyword recognition

Translate language

  • Translate text and documents by using the Translator service

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

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

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

  • Translate to multiple languages simultaneously

Build and manage a language understanding model

  • Create intents and add utterances

  • Create entities

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

  • Optimize a Language Understanding (LUIS) model

  • Integrate multiple language service models by using Orchestrator

  • Import and export language understanding models

Create a question answering solution

  • 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

  • Create a multi-domain question answering solution

  • Use metadata for question-and-answer pairs

Implement knowledge mining solutions (5–10%)

Implement a Cognitive Search solution

  • Provision a Cognitive Search resource

  • Create data sources

  • Define an index

  • Create and run an indexer

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

  • Manage knowledge store projections, including file, object, and table projections

Apply AI enrichment skills to an indexer 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 incremental enrichment

Implement conversational AI solutions (15–20%)

Design and implement conversation flow

  • Design conversational logic for a bot

  • Choose appropriate activity handlers, dialogs or topics, triggers, and state handling for a bot

Build a conversational bot

  • Create a bot from a template

  • Create a bot from scratch

  • Implement activity handlers, dialogs or topics, and triggers

  • Implement channel-specific logic

  • Implement Adaptive Cards

  • Implement multi-language support in a bot

  • Implement multi-step conversations

  • Manage state for a bot

  • Integrate Cognitive Services into a bot, including question answering, language understanding, and Speech service

Test, publish, and maintain a conversational bot

  • Test a bot using the Bot Framework Emulator or the Power Virtual Agents web app

  • Test a bot in a channel-specific environment

  • Troubleshoot a conversational bot

  • Deploy bot logic