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AI-102T00 - Designing and Implementing a Microsoft Azure AI Solution

Overview

Duration: 4.0 days

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The Certification & Training course will use C# or Python as the programming language.

Objectives

  • Define artificial intelligence
  • Understand AI-related terms
  • Understand considerations for AI Engineers
  • Understand considerations for responsible AI
  • Understand capabilities of Azure Machine Learning
  • Understand capabilities of Azure Cognitive Services
  • Understand capabilities of the Azure Bot Service
  • Understand capabilities of Azure Cognitive Search
  • Provision Cognitive Services resources in an Azure subscription.
  • Identify endpoints, keys, and locations required to consume a Cognitive Services resource.
  • Use a REST API to consume a cognitive service.
  • Use an SDK to consume a cognitive service.
  • Consider authentication for Cognitive Services
  • Manage network security for Cognitive Services
  • Monitor Cognitive Services costs
  • Create alerts
  • View metrics
  • Manage diagnostic logging
  • Create Containers for Reuse
  • Deploy to a Container
  • Secure a Container
  • Consume Cognitive Services from a Container
  • Detect language
  • Extract key phrases
  • Analyze sentiment
  • Extract entities
  • Extract linked entities
  • Provision a Translator resource
  • Understand language detection, translation, and transliteration
  • Specify translation options
  • Define custom translations
  • Provision an Azure resource for the Speech service
  • Use the Speech-to-Text API to implement speech recognition
  • Use the Text-to-Speech API to implement speech synthesis
  • Configure audio format and voices
  • Use Speech Synthesis Markup Language (SSML)
  • Provision Azure resources for speech translation.
  • Generate text translation from speech.
  • Synthesize spoken translations.
  • Provision Azure resources for Language Understanding
  • Define intents and utterances
  • Define entities
  • Use patterns to differentiate similar utterances
  • Use pre-built models
  • Train, test, publish, and review a Language Understanding app
  • Set publishing configuration options for a Language Understanding app
  • Process predictions from a Language Understanding app
  • Deploy a language understanding app in a container
  • Understand Language Understanding and Speech service integration
  • Perform intent recognition with the Speech SDK
  • Understand question answering
  • Compare question answering to language understanding
  • Create a knowledge base
  • Implement multi-turn conversation
  • Test and publish a knowledge base
  • Consume a knowledge base
  • Implement active learning
  • Create a question answering bot
  • Understand principles of bot design
  • Use the Bot Framework SDK to build a bot
  • Deploy a bot to Azure
  • Understand dialogs
  • Plan conversational flow
  • Design the user experience
  • Create a bot with the Bot Framework Composer
  • Provision a Computer Vision resource
  • Analyze an image
  • Generate a smart-cropped thumbnail
  • Describe Video Analyzer for Media capabilities
  • Extract custom insights
  • Use Video Analyzer for Media widgets and APIs
  • Provision Azure resources for Custom Vision
  • Understand image classification
  • Train an image classifier
  • Provision Azure resources for Custom Vision
  • Understand object detection
  • Train an object detector
  • Consider options for labeling images
  • Identify options for face detection, analysis, and identification
  • Understand considerations for face analysis
  • Detect faces with the Computer Vision service
  • Understand capabilities of the Face service
  • Compare and match detected faces
  • Implement facial recognition
  • Read text from images with the OCR API and Read API
  • Use the Computer Vision service with SDKs and the REST API
  • Develop an application that can read printed and handwritten text
  • Identify how Form Recognizer's layout service, prebuilt models, and custom service can automate processes
  • Use Form Recognizer's Optical Character Recognition (OCR) capabilities with SDKs, REST API, and Form Recognizer Studio
  • Develop and test custom models
  • Create an Azure Cognitive Search solution
  • Develop a search application
  • Implement a custom skill for Azure Cognitive Search
  • Integrate a custom skill into an Azure Cognitive Search skillset
  • Create a knowledge store from an Azure Cognitive Search pipeline
  • View data in projections in a knowledge store

Audience

Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.

Content

1. Prepare to develop AI solutions on Azure

As an aspiring Azure AI Engineer, you should understand core concepts and principles of AI development, and the capabilities of Azure services used in AI solutions.

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2. Create and consume Cognitive Services

Azure Cognitive Services enable developers to easily add AI capabilities into their applications. Learn how to create and consume these services.

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3. Secure Cognitive Services

Securing Cognitive Services can help prevent data loss and privacy violations for user data that may be a part of the solution.

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4. Monitor Cognitive Services

Azure Cognitive Services enable you to integrate artificial intelligence into your applications and services. It's important to be able to monitor Cognitive Services in order to track utilization, determine trends, and detect and troubleshoot issues.

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5. Deploy cognitive services in containers

Learn about Container support in Cognitive Services allowing the use of APIs available in Azure and enable flexibility in where to deploy and host the services with Docker containers.

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6. Extract insights from text with the Language service

The Language service enables you to create intelligent apps and services that extract semantic information from text.

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7. Translate text with the Translator service

The Translator service enables you to create intelligent apps and services that can translate text between languages.

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8. Create speech-enabled apps with the Speech service

The Speech service enables you to build speech-enabled applications. This module focuses on using the speech-to-text and text-to-speech APIs, which enable you to create apps that are capable of speech recognition and speech synthesis.

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9. Translate speech with the speech service

Translation of speech builds on speech recognition by recognizing and transcribing spoken input in a specified language and returning translations of the transcription in one or more other languages.

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10. Create a Language Understanding app

The Language Understanding service enables you to train a language model that apps can use to extract semantic meaning from natural language.

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11. Publish and use a Language Understanding app

After creating a Language Understanding app, you can publish it and consume it from client applications.

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12. Use Language Understanding with Speech

While many applications work with text-based natural language input, it's also for applications to support speech. You can integrate the Language Understanding and Speech services to accomplish this.

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13. Build a question answering solution

The question answering capability of the Language service makes it easy to build applications in which users ask questions using natural language and receive appropriate answers.

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14. Create a bot with the Bot Framework SDK

Learn how to build a bot by using the Microsoft Bot Framework SDK.

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15. Create a Bot with the Bot Framework Composer

User the Bot Framework Composer to quickly and easily build sophisticated conversational bots without writing code.

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16. Analyze images

With the Computer Vision service, you can use pre-trained models to analyze images and extract insights and information from them.

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17. Analyze video

Azure Video Analyzer for Media is a service to extract insights from video, including face identification, text recognition, object labels, scene segmentations, and more.

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18. Classify images

Image classification is used to determine the main subject of an image. You can use the Custom Vision services to train a model that classifies images based on your own categorizations.

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19. Detect objects in images

Object detection is used to locate and identify objects in images. You can use Custom Vision to train a model to detect specific classes of object in images.

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20. Detect, analyze, and recognize faces

The ability for applications to detect human faces, analyze facial features and emotions, and identify individuals is a key artificial intelligence capability.

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21. Read Text in Images and Documents with the Computer Vision Service

Azure's Computer Vision service uses algorithms to process images and return information. This module teaches you how to use the OCR API and Read API.

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22. Extract data from forms with Form Recognizer

Form Recognizer uses machine learning technology to identify and extract key-value pairs and table data from form documents with accuracy, at scale. This module teaches you how to use the Azure Form Recognizer cognitive service.

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23. Create an Azure Cognitive Search solution

Unlock the hidden insights in your data with Azure Cognitive Search.

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24. Create a custom skill for Azure Cognitive Search

Use the power of artificial intelligence to enrich your data and find new insights.

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25. Create a knowledge store with Azure Cognitive Search

Persist the output from an Azure Cognitive Search enrichment pipeline for independent analysis or downstream processing.

Click here to know more

Prerequisites

Before attending this course, students must have:

  • Knowledge of Microsoft Azure and ability to navigate the Azure portal
  • Knowledge of either C# or Python
  • Familiarity with JSON and REST programming semantics

To gain C# or Python skills, complete the free Take your first steps with C# or Take your first steps with Python learning path before attending the course.

If you are new to artificial intelligence, and want an overview of AI capabilities on Azure, consider completing the Azure AI Fundamentals certification before taking this one.

Certification

Microsoft Certified: Azure AI Engineer Associate

Schedule

Scheduled DateCountryLocationFeesRegister
2022-10-04 - 2022-10-07 Philippines Virtual ILT PHP 31250
2022-10-11 - 2022-10-14 India Virtual ILT INR 60000
2022-10-24 - 2022-10-27 Indonesia Virtual ILT IDR 16000000
2022-10-25 - 2022-10-28 Thailand Virtual ILT THB 16000
2022-10-25 - 2022-10-28 Singapore Virtual ILT SGD 2800
2022-10-25 - 2022-10-28 Australia Virtual ILT AUD 2800
2022-11-08 - 2022-11-11 Sri Lanka Virtual ILT USD 600
2022-11-14 - 2022-11-23 United Arab Emirates Virtual ILT USD 1000
2022-11-29 - 2022-12-02 Malaysia Kuala Lumpur MYR 3000
2022-11-29 - 2022-12-02 Malaysia Virtual ILT MYR 3000



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